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#multiple choice questions on data collection
yesthattoo · 6 hours
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Survey recruitment; I gave feedback as a later consultant & Tuttle is another Autistic AAC user who was involved in the project from the start. Shares are Definitely Helpful :)
Are you an autistic adult who uses speech and other tools (such as augmentative and alternative communication [AAC]) to communicate?
If you answered yes, please consider participating in this survey at this link:
We are interested in learning about the speech, AAC, and assessment experiences of autistic people who use speech and AAC. We are curious if a modified version of the Communicative Participation Item Bank (CPIB) can be a reliable tool for clinicians to utilize in measuring the internal experiences of speaking autistic people. Regarding assessment, we are interested in understanding how their speech efficacy, or the extent to which one can use speech to completely communicate their intended meaning, was measured and considered in the evaluation process and if the evaluation resulted in a recommendation of an AAC tool.
The survey includes a mix of multiple choice, slider, and written response questions and is estimated to take between 10-20 minutes.
No identifying information will be collected in this survey.
Please reach out with any questions or concerns via email.
We thank you in advance for contributing your insight on this important topic!
Karina Rayl, B.S. (Lead Investigator)
Graduate Student
Speech and Hearing Sciences
Portland State University
Pang Lee Herr, B.S. (Lead Investigator)
Graduate Student
Speech and Hearing Sciences
Portland State University
Brandon Eddy, M.A., CCC-SLP (Co-investigator and Faculty Advisor)
Associate Clinical Professor
Speech and Hearing Sciences
Amy Donaldson, Ph.D. CCC-SLP (Co-investigator and Faculty Advisor)
Associate Professor
Speech and Hearing Sciences
Tuttle (External Collaborator)
Alyssa Zisk, Ph.D. (External Collaborator)
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flecks-of-stardust · 3 months
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Independent Research on Experiences with Imaginary Friends
Hello Tumblr! Some of you may have seen this poll I made going around. As of writing this post, the poll is still going, so if you haven't voted and would like to you are more than welcome to do so. However, this post is to more formally announce the survey I made that expands on the idea behind the creation of the poll; you can access it here.
The survey polls on experiences with imaginary friends, but also includes questions about social experiences and neurodivergencies, in particular system experiences. You do not need to be a system to respond to this, and in fact I encourage singlets to also take the survey. People of all neurotypes and all ages are allowed to respond to the survey. The survey is primarily multiple choice with avenues to elaborate on your selections, but it also has three long answer questions. The whole survey should take around 15 to 20 minutes to complete. You are encouraged to be as specific as possible, even if you're not sure about how to answer a question.
All responses collected will be seen by my eyes only, and will be analyzed only by me; this endeavor is a one person effort. The data gathered by this survey will not be formally published. At best, if enough people wish to see the results, the results and analysis will be posted on Tumblr, on this same blog.
It would be much appreciated if this post is spread around, but I highly, highly encourage you to share the link to the survey outside of Tumblr as well. Data collection will cease on March 1st, 2024 or when there are 500 responses, whichever comes first.
Thank you in advance for indulging my curiosity!
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39oa · 4 months
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nhl x f1 fandom survey results
hello there! about two months ago, @andreisvechnikov and i posted a form meant to gather data from fans on tumblr of both f1 and the nhl so we could take a look at demographics, trends, and then subsequently share interesting corresponding insights.
in total, our form received n = 102 responses — honestly not that great of a sample size for stratifying data by teams when considering that there are 32 nhl teams and 10 f1 teams, so a lot of findings come with a large caveat, but hopefully this post will be interesting to you anyway! (of note is also that all of this data was collected before the nhl regular season began, so hopefully we can rerun this experiment sometime next year when the seasons are running concurrently and see how results have changed then.)
unrelated to our survey, @sergeifyodorov also polled hockey fans on their favorite teams a while back; his results will be referenced as well throughout this post! he was extremely kind and generous enough to send over his data so that we could play around with it on our own, so thank you again for that!!! one last time, please note that our results are not easily comparable because of different sample sizes and team/blog reach (for example: the leafs were heavily underrepresented in our data, but i'm pretty sure it's because the form simply never made its way to that corner of hockeyblr and not because leafs fans are statistically less likely to enjoy f1 LOL...)
without further ado:
DEMOGRAPHICS
"Where do you currently live?" + "How old are you?"
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out of 102 participants, an overwhelming amount — 85.3% — live in north/central america or europe, and most respondents were also between the ages of 18-25. since the nhl is based in north america and f1 teams are (mostly) based in europe, i was curious to see how fandom trends varied across these two demographics specifically.
EUROPE VS. AMERICA
"Do you consider yourself more of an F1 or hockey fan?"
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interestingly enough, 2 in 3 of the european respondents said that they like or follow hockey more, with only 15.15% preferring f1. asian and north/central american fans were a little more evenly split, with 38.9% north/central american fans saying they liked f1 and hockey about the same. however, altogether 89.2% of global respondents said that they prefer hockey OR that they like both sports about the same, so it seems that fans in our survey skew more toward hockey in general.
"Do you follow any top-division hockey leagues outside of North America?"
again, since f1 is primarily based in europe and since europe boasts a huge hockey market outside of the nhl, this question was aimed at understanding interest in other top-division hockey leagues outside of north america. more specifically — not anything like the ahl or ncaa but instead leagues like the shl and liiga.
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the majority of the respondents who said they followed top-division hockey outside of north america were, unsurprisingly, based in europe, with over half (54.5%) claiming to follow other leagues and 1 in 4 (24.2%) preferring these to north american hockey.
as for north/central american respondents, a large majority — 85.2% — claimed to not follow any leagues outside of north america. here were the leagues mentioned at least twice:
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"Do you follow professional leagues for any of these following sports?"
for this question, we gave several multiple-option choices of obvious sports and also allowed respondents to submit their own answers if we missed any. here were the most-commonly followed professional sports outside of f1 and the nhl, filtered to at least 2 responses:
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interestingly, football and baseball were on par at 26.5% — or about 1 in 4 — each, although the most common response was actually none; 37.3% of respondents said they only watch hockey and motorsports for professional sports. the sports that received one vote each were: volleyball, tour de france, swimming, pro wrestling, gymnastics, figure skating, cycling, climbing, and australian rules football.
TEAM POPULARITY
NHL STATS
"What is your favorite NHL team?" + "If you like multiple NHL teams, feel free to name any others below." (<;- capped at 3)
in order to rank each team — despite different voting methodology and sample sizes from both surveys — i normalized a popularity score based on a weighted value, composed of how many people voted for it as their favorite team and then how many people mentioned it in the "other teams i like" question. each team was then graded relative to the top team, in our case dallas and in cody's case pittsburgh.
in the table below, the numbers in purple correspond to our survey and the numbers in grey show cody's results as reference. as you can see, toronto is very underrepresented in our data, while dallas is considerably more popular and tops the chart. 3rd-place vancouver was also our most commonly mentioned "other" team with 19 votes, despite only being 6 people's favorite team.
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does this mean that fans of both f1 and hockey are statistically more likely to enjoy dallas than your average hockey fan? or does it just mean that i'm primarily a dallas stars blog and this was the audience i accidentally reached when sharing my survey? (most likely the second) the world may never know!!!
another way of looking at the popularity differences across both surveys is with a little scatter plot. same data, just different presentation!
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F1 STATS
"What is your favorite F1 team?" + "If you like multiple F1 teams, feel free to name any others below."
not much that needs to be explained here — mercedes and ferrari were far and away the favorites, but red bull and mclaren were also fairly popular! the least popular team of all was haas, with only one person mentioning it as a team they liked and no one voting for it as their favorite team.
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interestingly enough, 1 in 3 (34) of respondents said that they had no favorite team at all, with this response scoring higher than any single team (mercedes only had 21 "favorite" votes, although it had 36 total responses). this was a large contrast to the nhl results, where only 6 people answered none for their favorite hockey team — meaning that 94.11% of respondents claimed a favorite nhl team!
(perhaps this means that f1 fans are less likely to be loyal to a team and instead prefer to follow drivers' individual careers, or that team allegiances are simply stronger in hockey fandom. or maybe not! who knows.)
something else i was curious to see concerning the most popular teams was another location distribution, although this time i didn't want to simply calculate percentages straight-up since we already know that the global distribution skews mainly toward north/central america and europe. because of this, i filtered only teams that had n >= 10 votes and calculated the difference for each percentage from the global average, so i could see which teams were more biased toward a location than "expected."
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for f1: ferrari, mclaren, and red bull all had slightly higher american interest than average, with red bull especially skewing lower on the european side.
for hockey: dallas had higher than average interest in oceania, with pittsburgh scoring higher in asia and seattle being especially strong in north/central america (and thus less so in europe). toronto, carolina, and florida also had higher support in europe.
(note again that these are very small sample numbers, especially for teams with less than 20 votes!)
+ just for fun, here's how the top 4 other sports (football, baseball, american football, and basketball) skewed location-wise.
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probably not much of a surprise here, although interestingly europeans were more likely than americans to say they only followed motorsport and hockey.
PLAYER / DRIVER POPULARITY
"Who are your favorite NHL players?" + "Who are your favorite F1 drivers?"
when it came to calculating the most popular players, we asked that survey respondents list up to three of their favorite players, then assigned 3 points to the first player, 2 to the second, and 1 to the third. using this weighted count, i ranked drivers and players using a normalized score.
86 unique nhl players were mentioned for this question. out of them, 84.9% (73) are still actively playing in the nhl. the most popular active players were sidney crosby and quinn hughes, while the most popular inactive player was paul kariya, with 2 mentions and a score of 11.76%.
using the same process, 39 unique f1 drivers were mentioned for this question, this time with 95% (19/20) of the current grid being represented — the only driver not mentioned a single time was nico hülkenberg. the remaining 20 drivers were either retired or reserve drivers. lewis hamilton was far and away the most popular driver in this survey, while the most popular inactive driver was 3rd-placed sebastian vettel with a relative score of 61.18%.
here are the top 25 for each sport alongside their corresponding teams:
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as you can see, the most-represented team in the nhl top-25 is dallas, with 4 players (robertson, hintz, heiskanen, oettinger) making the cut! other teams to have at least 2 athletes in the top 10 are edmonton for the nhl and alphatauri for f1.
F1 X NHL CROSSOVER
this was the main reason we created this survey in the first place. our burning question was: Which F1 teams do fans of certain NHL teams tend to like — and vice versa?
in order to calculate this, i mapped all the nhl teams each respondent voted for to all the f1 teams they voted for, assigning 1 point to each. so if someone had a favorite team and named three "other" liked teams for each sport, that would be 8 points on the matrix altogether. i then filtered out any nhl team that had less than 20 total tallies for f1 teams and created the chart below:
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i also removed "none" votes since i was more interested in the distribution of interest strictly across f1 teams. finally, i filtered out the f1 teams with negligible amounts of votes and created another percentage chart relative to the global average (since we "expect" mercedes and ferrari to be most popular overall):
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some summarizing thoughts:
DAL and VAN fans were both less interested in red bull and ferrari and more interested in mclaren and williams
NJD and PHI both voted less for mercedes; the former preferred ferrari and the latter red bull
CAR didn't have huge discrepancies across the board, but skewed a bit toward red bull and williams
COL had the lowest relative interest in mclaren of all teams, while SEA had the highest relative interest in williams
again, these sample sizes were pretty small so maybe it means nothing at all. i'd love to run this survey again with more responses and maybe also restrict the team choices to only 1 favorite + 1 other team per sport in order to really drill down into people's preferences, but hopefully this is interesting anyway!
FANDOM ORIGINS
i always love learning about how people got into a fandom, so we also asked respondents how they got into f1 and hockey, with the following options being provided:
Grew up around it/Family
Hockey or F1 RPF
Introduced by friends (online or IRL)
Discovered individually through fandom content (gifs, YouTube, podcasts, etc.)
Hockey books & romances (Hockey)
Drive to Survive (F1)
Other films, documentaries, etc.
3 respondents clarified that they specifically discovered hockey through reading the webcomic check, please!, but i decided to implicitly include this in the "hockey books" category. a few of the "other" options for hockey also specifically mentioned the olympics.
here was the distribution of responses, noting that the question was multi-option so there is overlap:
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i also made a side-by-side bar chart to note differences between f1 and hockey origins. in this case, i paired "hockey books/romances" with "drive to survive," since i see them as the two biggest respective examples of mainstream media movements for each fandom (around social media/rps spaces i should say), the former being mainly based in booktok.
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as you can see here, a considerable amount of fans got into f1 through dts (1 in 5). in terms of fanfiction, hockey rpf was a lot more influential in getting people into hockey than f1 rpf was in getting people into f1 (23.7% vs. 11.3%). lastly, hockey was also slightly more common as a childhood/family sport than f1, although only by a few percentage points — 28.9% of fans grew up with hockey and 23.2% grew up with f1.
of course, i couldn't end this question without doing another location analysis, which gave some interesting results:
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for f1, the overwhelming majority of european respondents said that they grew up around f1 or were introduced to it by family — 51.5%, or over half (the chart says 44.7% because of multi-option overlap). in contrast, only 24.1% — or 1 in 4 — of north/central americans said this. their results were much more evenly split in general, with drive to survive and fandom content ranking considerably higher.
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for hockey, the distribution actually looked quite similar between north/central americans and europeans, although americans ranked a little higher in terms of growing up around the sport. it's pretty much the same though — the main difference is that a good chunk of the "other" votes for the europeans specified getting into hockey through the olympics. altogether, respondents from asia, oceania, and south america mostly discovered hockey through a mixture of rpf and hockey books, although these are very small sample sizes so not fully reflective of overall experiences.
OTHER MOTORSPORTS
"What other motorsports do you follow?"
we were also interested in knowing what other kinds of motorsport people liked.
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interestingly, north/central americans had the smallest proportion of f1-exclusive respondents, with 37.7% saying f1 is the only motorsport they follow. here were the series that received at least 10 votes:
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indycar was by far the most popular "other" motorsport series, with motogp, nascar, and general feeder formulae (f2, f3, etc.) faring well too. unsurprisingly, you can also tell at a glance that there is overwhelming american interest in indycar and nascar compared to other series!
CONCLUSION
that's about all we've got at the moment. if there's anything else you'd like to see more of, or anything you're confused about/think doesn't make sense, feel free to reply to this post or shoot me an ask :') thank you again for reading and i hope you enjoyed this little post!!! 🥲❤️
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wiltingdecay · 10 months
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hello arcana fandom 👍 soooo i've been curious about our ocs and what patrons they have for a while now, particularly after noticing several patterns in the fandom; for example, almost nobody seems to have their oc share a patron with one of the m6. because of that, and because i've always had an interest in data collection, i decided to make a patron Arcana survey!
there are only two questions, but the only required question is, obviously, the one where you state which of the arcana you chose as your oc's patron. there's also an optional question where you can explain the thought behind your choice/gush about your blorbo in general. multiple responses are enabled, so if you have more than one oc, feel free to resubmit the survey for all of them.
i will not do anything with the results (aside from maybe posting them on here of course) they are just for me to look at and go "oh neat :]" so have fun with it!!
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straws-and-stats · 1 year
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In light of both the announcement of The Magnus Protocol and the introduction of polls to tumblr, I thought it would be a good time to reintroduce the fandom to Ye Olde TMA Fan Survey!
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If you weren’t one of the 3,500+ people able to take the survey back in the day and it sounds like something you’re interested in, I’ve got good news for you:
THE TMA FAN SURVEY IS STILL UP AND RUNNING!
Take the survey here (it contains spoilers through the finale!!!)
Read after the break for more context and for the results of the initial run!
Exactly two years ago, a group of us launched the TMA Fan Survey as part of the fan project Eye Love TMA to celebrate the podcast that means so much to so many. In the two months between survey launch and the March 2021 finale, we got over 3,500 fans (and a few cast/crew members!) to take the survey. I had a blast getting to examine such a large set of data and analyse how the fandom related to the podcast through items such as:
Favourite character
Favourite season
Scariest episode
Charisma levels of the fandom as compared to the Archivist
What the Admiral looks like
How the Admiral wears trousers
Which entity fans are most afraid of
Which dancing Theresa May haunts the Archivist in the gap between his nightmares
And so, so much more!
Now, since the fandom has only continued to grow since the finale, and that means there are even more people who are able to contribute to this project, I decided to readvertise the survey.
Through the launch of TMagP, I’m going to be running a drive to collect Even More Data for the survey and release an updated newsletter come October.
Look at the finale-era results here.
Tumblr post of highlights from newsletter launch by the incredible niksfake
Adorable comic by shanni used to advertise the survey
Just to note that, going forward, I’m only going to be looking at the multiple choice questions on the survey. I already read through 3,500 responses to each of the 6 short answer questions and I am not going to read through any more, thank you very much.
Also, the survey was written in between the release of MAG 190 and MAG 191 and updated relevant episode-centric questions with each new release, so please feel free to laugh at some of the more outdated questions.
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many-but-one · 2 years
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System Partner Boundaries Survey
Hello everyone! This is Dorian from Many but One. Recently in a system server I am part of, a lot of members were talking about boundaries with partners. Systems in the server were talking about the various ways their partners either respected or denied their boundaries. Some people said their partner was amazing and acknowledged every alter's boundaries. Others said their partners violated alter boundaries at almost every turn with little to no remorse for the actions.
As some of you know, I write articles for a website called "The Mighty" for people with DID. I have several articles waiting for review and publication, and one article fully published (it can take months for articles to be reviewed, as their team is small). The article I have published is another guide for people whose partner just came out as a system. My therapist has read and reviewed it and said it's a great "first resource" for partners, as it first talks a bit about what DID is, and then gives a short list of tips at the end. You can read "Tips for When Your Partner Has DID" at this link.
What is my article about?
I will be writing a guide for partners of DID systems AND for DID systems to help them work on boundaries. A lot of non-systems don't understand the idea of boundaries with individual alters and I want to help explain it to them as well as help folks with DID talk about how to set boundaries with their partners. My goal with this data I'll be collecting is to share how proper boundaries affect people with DID and how violating boundaries affects people with DID.
To be absolutely transparent about this survey:
-Answers are fully anonymous. You will have to sign in with a gmail/email account but that will NOT be shared with me at all.
-All questions are required to be answered except the LAST TWO, which are paragraph-style answers, one of which asking for any additional information you'd like to share about how you and your partner set boundaries with each other and the other asking for any feedback on the survey as a whole. These two questions will NOT be used in ANY data for the article.
-There are ELEVEN required answers, plus the two optional answers, making the quiz thirteen questions long total. It will likely take about 5-10 minutes to complete depending on if you write in your own answers or not. One of the eleven required answers is simply consent to use the data you provide for my article.
-This data (the multiple choice questions) will be compiled and used for my article, to give people "real life" data from a sampling of people who have a complex dissociative disorder (CDD). No data will be tied to you specifically, ever. It will be more like graphs or percentage data rather than specific answers from specific people. There will be a disclaimer in the article that this is a sampling from a population of people with DID, but NOT an accurate "scientific" sampling, as I can't prove everyone who participates has DID with certainty.
-There are several questions which will require a concrete answer from the given answers. There are also several questions with an "other" option to allow you to fill in the blank with your personal experience. If you do so, please know that any identifying information will be seen by myself and other survey-takers, as the survey results WILL be able to be viewed after survey-takers are finished. If identifying information is presented, it will NOT be used in the article. For any graphs it would simply be labeled as "other" and if the personal experience feels like a relevant point to make in my article, then it may be paraphrased with NO identifying information shared.
-The survey will be open until October 15th. Shortly after it closes, all data will be compiled in graphs and all that fun stuff. I will then write the article. I will publish it here, as well as submit it to The Mighty for review. If the article is accepted I will also publish the link to the article on The Mighty's website here and on other social media.
Who Can Take the Survey?
-You must have a CDD (complex dissociative disorder) that includes DID, OSDD, P-DID, UDD, etc. You can be officially diagnosed, medically recognized, or self diagnosed with research. This survey is for people who are traumagenic.
-You must have a partner or spouse. It doesn't have to be a single partner or spouse. Poly relationships are accepted as well. This survey is NOT for familial relationships or for friendships. (I may do a separate one for a different article about family/friend relationship boundaries with DID systems.)
-This is specifically for people in a relationship. QPP (queer platonic partnerships), romantic relationships, and sexual relationships are all accepted. Even if the relationship is not a "committed" or "long-lasting" relationship, (i.e. "friends with benefits") I would be interested in hearing your input, as boundaries are necessary for all of the above, no matter how deeply committed you are with the person.
-Past relationships work too! If you have been in a relationship in the past but are not anymore, that works as well!
The Survey
I'm going to tag some folks to see if they are willing to boost this post so I can get a large sampling of data. Those that I tag, you are NOT required to share/reblog/etc! Thank you if you do!
@did-inquiry @circulars-reasoning @holywheel @foreverfragmented @the-cabin-complex @dissociativediscourse @ultrabright-flashlight
Edit: If you would like a transcript of the questions in the survey before clicking the link, please DM me and I would be happy to provide that for you!
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NASA's trio of mini rovers will team up to explore the Moon
Working together without direct human input, three rovers each the size of a carry-on bag will map the lunar surface in 3D, using cameras and ground-penetrating radar.
NASA is sending a trio of miniature rovers to the Moon to see how well they can cooperate with one another without direct input from mission controllers back on Earth. A teamwork-minded experiment to demonstrate new technology, the CADRE (Cooperative Autonomous Distributed Robotic Exploration) project marks another step the agency is taking toward developing robots that, by operating autonomously, can boost the efficiency of future missions. And, by taking simultaneous measurements from multiple locations, the rovers are meant to show how multirobot missions could potentially enable new science or support astronauts.
Currently slated to arrive aboard a lander in 2024 as part of NASA's CLPS (Commercial Lunar Payload Services) initiative, CADRE's three small rovers will be lowered onto the Reiner Gamma region of the Moon via tethers. Each about the size of a carry-on suitcase, the four-wheeled rovers will drive to find a sunbathing spot, where they'll open their solar panels and charge up. Then they'll spend a full lunar day - about 14 Earth days - conducting experiments designed to test their capabilities.
"Our mission is to demonstrate that a network of a mobile robots can cooperate to accomplish a task without human intervention - autonomously," said Subha Comandur, the CADRE project manager at NASA's Jet Propulsion Laboratory in Southern California. "It could change how we do exploration in the future. The question for future missions will become: 'How many rovers do we send, and what will they do together?'"
Mission controllers on Earth will send a broad directive to the rovers' base station aboard the 13-foot-tall (4-meter-tall) lander. Then the team of little robots will elect a "leader," which in turn will distribute work assignments to accomplish the collective goal. Each rover will figure out how best to safely complete its assigned task.
"The only instruction is, for example, 'Go explore this region,' and the rovers figure out everything else: when they'll do the driving, what path they'll take, how they'll maneuver around local hazards," said JPL's Jean-Pierre de la Croix, CADRE's principal investigator. "You only tell them the high-level goal, and they have to determine how to accomplish it."
Experiments in Teamwork
The rovers will face several tests - all within view of a monitoring camera on the base station atop the lander. The first is to drive in formation and stay on course using ultra-wideband radios to maintain their relative positions while relying on sensors to avoid obstacles. In a second experiment, the rovers will each take a path of their own choosing to explore a designated area of about 4,300 square feet (400 square meters), creating a topographic 3D map with stereo cameras. The project will also assess how well the team would adapt if a rover stopped working for some reason. Success will indicate that multirobot missions are a good choice for exploring hazardous but scientifically rewarding terrain.
And while CADRE isn't focused on conducting science, the rovers will be packing multistatic ground-penetrating radars. Driving in formation, each rover will receive the reflection of radio signals sent by the others, creating a 3D image of the structure of the subsurface as much as 33 feet (10 meters) below. Together they can gather more complete data than can current state-of-the-art ground-penetrating radars like the one on NASA's Perseverance Mars rover, RIMFAX (Radar Imager for Mars' Subsurface Experiment).
"We'll see how multiple robots working together - doing multiple measurements in different places at the same time - can record data that would be impossible for a single robot to achieve," Comandur said. "It could be a game-changing way of doing science."
Working Smart
But there's more to CADRE than testing autonomy and teamwork capabilities: The rovers also need to survive the harsh thermal environment near the Moon's equator, which poses a challenge for such small robots. In the searing sunlight, the rovers could face midday temperatures of up to 237 degrees Fahrenheit (114 Celsius). Made with a combination of commercial off-the-shelf parts and custom-built components, the rovers must be robust enough to make it through the daytime heat while being compact and lightweight.
At the same time, they need to have the computing power to run the JPL-developed cooperative autonomy software. It's a difficult balance: The project's rovers and base station get their brain power from a small processing chip (the next generation of the cellphone-class processor inside NASA's Ingenuity Mars Helicopter), but using the processor contributes to the heat.
To prevent the rovers from cooking, the CADRE team came up with a creative solution: 30-minute wake-sleep cycles. Every half-hour, the rovers will shut down, cooling off via radiators and recharging their batteries. When they simultaneously awaken, they'll share their health status with one another via a mesh radio network (much like a home Wi-Fi network) and once again elect a leader based on which is fittest for the task at hand. Then off they'll go for another round of lunar exploration.
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askagamedev · 1 year
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In game development, it is common for the person in charge to make a final decision and therefore overruling some devs in the process. In some posts of yours, you mentioned that you also have been overruled multiple times, and sometimes if was a mistake, but also sometimes is was the right choice. The last part interests me and my question is: Can you describe in which situations you are glad you have been overruled? It sounds like a strong learning moment realizing ones own mistake much later.
Sure. I can definitely recall one such situation - it was certainly an educational epiphany for me because it forever changed how I saw the work. I was working on a pretty well-established MMOG at the time. Like most successful MMOGs, it had a lot of major gameplay systems. I had a personal fondness for a particular one of these gameplay systems so I was excited to pitch an idea expanding and improving on it. My lead gently rebuffed me and gave me perhaps one of the most important design lessons of my life. This is that lesson.
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One of the myths I used to believe about game design is "if you build it, they will come". I used to believe that pouring more resources into a particular type of content would entice more players to engage with that content. On paper, it made sense - if we spent more resources on it, we could make it cooler, more intuitive, more engaging, and get more players to play it. That was the essence of my pitch. Unfortunately, I had been running off of a combination of gut feeling and player discussions dedicated to the particular flavor of content I was talking about.
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My manager explained it to me - adding more resources would not necessarily see a 1:1 correlation to player engagement. Instead, what would happen would be that the small percentage of players that already engaged with that kind of content regularly would feel great at being fed more, and we'd get a one-time spike of players who would try it once and never go back. No one else would engage with the content. The fact it was a mature MMOG meant that they had years of collected data to back up those assertions.
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I wanted to believe that it was just because we didn't try hard enough or didn't put enough resources into it, but I had to face a hard truth - the devs who I had imagined weren't "trying hard enough" were my coworkers and teammates - the ones I knew, worked with, and trusted. It wasn't like we would magically conjure up super-designers from the ether who were far better at content creation than the existing team of seasoned professionals we already had. "Try harder, do better" wasn't a feasible solution once I actually had to consider what "try harder, do better" entailed. It wasn't going to be enough. It wasn't going to work.
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As you said, the realization that my core assumption was flawed was a very strong learning moment for me. A long-held bit of industry wisdom is the willingness to "kill your babies", and that day I had the realization that one of mine was quite undead. I am very thankful to my manager for teaching me that lesson that day. It has been some extremely valuable wisdom that I've used to help evaluate ideas, both proposed by others and my own.
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khaleesiofalicante · 29 days
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https://forms.gle/kcNPb7W6n5rLXy7GA
So this is my first survey I am conducting for a research paper...would you maybe like to fill it and tell if I should make any changes?
okay since you asked here is some feedback (please excuse if it's too much but tis my literal job to review shit and give feedback and I am very anal about it)
I'd edit the title of the survey into something more formal/academic. For eg: "An Examination of Sustainability Practices: Fashion versus Food Industries" (this needs work but just an example of how a survey title should be written.
In your description give definition of sustainability. Eg. "for purposes of this survey, we define sustainability as ABC (Source)"
There is an error in your age brackets. 18 is repeated twice.
For scale questions (such as Q1), give the options as statements "I don't think about it at all" "I think about it often" etc. When only one question has a scale like that in a survey it's often confusing and the format seems out of place. OR - use the 'linear scale' option for answers instead of 'multiple choice'.
For Q5, 'not aware' doesn't seem like an appropriate response. perhaps "I'm not sure" or "Unsure" make more sense.
Q6 - use likert scale instead of MC for options (for any rating it should be likert scale)
Q10/Q11 - feels like good questions to ask "other" and then add own answer - IF you are collecting quantitative data.
Check language and grammar for last question for eg it should "I've heard.." etc.
A very fascinating topic btw! Good luck with the survey!
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namechangesurvey · 3 months
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An Update!
Thank you for your patience while I sorted some things out. Here's the news:
The original survey that ran from 13th - 17th December will NOT reopen unfortunately. I'll be analysing the data collected so far (from just over 1400 completed surveys) for my thesis, but that's already a pretty tall task and it simply wouldn't be doable if the numbers were even higher.
However! I will be doing a SECOND SURVEY that is more streamlined and suitable for large numbers of participants!
You will no longer be asked to share your first names directly (or record yourself saying them out loud). The survey will instead consist mostly of single or multiple choice questions related to your name(s) and - if you've changed your name - the reasons they were chosen and your experiences with the change. You can participate in the second survey no matter whether you took the first one or not (it will basically serve as a comparison to the first one to see if certain trends in answers are the same)!
I'm currently working on this new version and will share it with you as soon as I'm done with it (along with a more detailed breakdown of what's different). And this time it won't close after a couple of days, promise! The plan is for it to stay open until early to mid January.
Stay tuned! :D
(Also my supervisor asked for a link to this blog to see what all the fuss is about over here on Tumblr, so EVERYBODY BEHAVE PLEASE lol)
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there’s a wonderful history book on this phenomenon by Ian Kershaw, Popular Opinion & Political Dissent in the Third Reich: Bavaria 1933-45, discussing polling, opinions, support and lack thereof in nazi germany through a targeted study of bavaria. one of the conclusions is that totalitarian societies never achieve a monopolistic control (thus one of the roots for the whole debate on the validity of “totalitarian” as an analytical term), but that many are too afraid to do more than “dissent,” kershaw dismissing such actions as resistance. on fear and frailty, he writes in the introduction: 
My own work was not so much concerned with this highly courageous though, unfortunately, miniscule and unrepresentative section of the population, but with the great mass of the ordinary population who tended to look on, sometimes no doubt with disapproval, and even more frequently to look away [from Nazi crimes and persecution]. Probably, had I been a German living at the time, I would have been one of them. Their very passivity, from motives ranging from tacit approval to fear of what might happen to them for signs of supporting the Jews, is, I was arguing, both understandable in itself and necessary to an explanation of how the radicalism of another minority - though certainly a far larger one than the opponents of racism, and with all the power of the state at its disposal - could so easily gather pace.
moving away from godwin’s law, you could also look to vladimir shlapentokh’s work on sociology in the soviet union. before emigrating, shlapentokh himself started out as a sociologist in the ussr:
Soviet sociologists, in effect, were aware that they had to deal with several ���realities” accepted by most people in the Soviet Union. One was the reality of their everyday life with all its difficulties, absurdities, and happy and distressing developments. Another reality appeared in people’s opinions given to pollsters. It was a more optimistic and positive vision of their lives and the world around them. Harsh criticisms and pessimistic views were carefully avoided. Finally, the third reality was the censored reality of party officials and ideologues. It was a reality containing perceptions of a strong and prosperous country supported by its people. In that picture, the Soviet Union was a country looking forward to its days of prosperity, international respect, and ideological unity. People lived in and knew only one social reality but reflected and spoke differently about it based on their individual ideological beliefs and specific position in the society.
[...] Shlapentokh, began his career as a Soviet sociologist who studied how the Soviet people developed their perception of the surrounding social world and which factors influenced their views. Of course, surveys could provide valuable information, but could the Soviet people tell a pollster what they truly thought? When Shlapentokh began to design the questions for the first national surveys in 1966–1969 (the respondents were the subscribers of the daily Izvestia, one of the most circulated papers in the Soviet Union), he tried to use several methodological devices to find out the actual, uninhibited views and feelings of the respondents. He compared the answers that the respondents gave at work, at home, in written mailed questionnaires, and in face- to- face interviews, answering both multiple- choice and open- ended questions. Shlapentokh and other Soviet sociologists (among them Boris Grushin and Vladimir Yadov) were able to describe, on the basis of their empirical data collected in the 1960s, how the Soviet people perceived the official image of Soviet society and how they tried to “adjust” their answers to the questions in the surveys: Many respondents did not accept the official picture of their society but tried not to reveal their true, mostly critical, views. Using various survey techniques, the Soviet sociologists were able to describe a variety of critical views of the regime: Some of them were ultraconservative and demanded “more Leninism” and “more communism”; others were nationalistic and chauvinistic; and others were clearly pro- Western. Contrary to what the Soviet propaganda claimed and many people in the West believed, there was no monolithic opinion about their country held by all the Soviet people.
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derridoid · 7 months
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Very interested in your thesis 👀
ALRIGHT. putting this under the cut because it's A Lot and i don't wanna clog up your dash. but i'll go ahead and pop in the link to my thesis here! tl;dr - 80 pages of scholarly research that answers the question "why do people use tumblr?"
so, because i'm a grown up with a considerable presence on the web, i'll share some potentially personal info. i don't have any concerns about being doxxed or anything like that lmao this is tumblr dot com.
i completed my masters degree about a year ago at bowling green state university. bgsu is one of the few institutions in this area of the country that has programs for cultural studies, so it was a great fit for me.
my thesis's goal was to use qualitative, humanistic research methods to understand the broad culture of tumblr - that is to say, i wanted to study people and their experiences on the site. basically, my thesis advisor and i sat down and asked, "what the fuck is up with tumblr?" and developed a research methodology to answer this question. my methods were inductive, meaning that i went in and gathered data, took a look at my notes, and generated a conclusion that answered the question.
i did it within the realm of "constructivist grounded theory," which is a specific way to apply inductive reasoning to humanistic research. it focuses on how experiences construct meaning and value; people don't inherently give sites like tumblr value, they use it in a way that creates that for them. the basic steps of the research method are as follows: go over your literature to get an idea for what you're up to, collect your data (in my case, interview users of tumblr), "code" your data (go over the transcripts word by word and look for similarities/draw conclusions), go back into the field and interview MORE people, and then draw a conclusion that answers your question (which is usually "what is up with this thing").
i'm really proud of my thesis and the "theory of tumblr" i came up with (which i'll put in a blockquote at the end of this answer), but there are some things i'd change in the future if i go on to do a phd. i would have liked to go back out into the field to interview more people - i didn't have time for this since i only had two semesters to write my thesis lmao. i also would have liked to get a broader sample size. i was deep into bandom hell, so a lot of my research participants were in that subculture as well. they were all also personal acquaintances and friends - it would have been nice to interview perfect strangers! i guess my theory of tumblr is more "theory of a handful of people in my bubble who are part of a very specific subculture and all have very similar demographic/social backgrounds"
if anyone wants to build off this research, i recommend setting a survey out into the wild on tumblr and THEN doing interviews. give it a nice mix of multiple choice/slider questions as well as some short answer questions. look for overarching themes and similarities in all those responses! and maybe make one of your survey questions "can we reach out to you with further questions?" so you can do interviews that are more in depth. interview a few people at a time, see what they say, and then go out and interview more people and see if they say the same thing. don't be afraid to update your research question or change what themes you focus on. if your findings are different than what you expect, that means you're onto something cutting edge!
also - i TOTALLY recommend doing interview via zoom like i did. if you have a premium subscription, it'll generate a transcript for you in real time, so you don't have to sit down, listen to the audio, and transcribe it chunk by chunk. makes coding WAY easier.
as promised: my academic "theory of tumblr":
Tumblr is a microblogging social media platform that has been turned by users into an emergent space for community development, cultural creation, and identity affirmation. The aspects of the site that prove significant to its construction and userbase include but are not limited to the userbase’s focus on social engagement through shared interests and worldviews, the uniqueness of the site’s design, the prioritization of marginalized and diverse people, and the performance and refinement of user identities. These nuances of Tumblr have made it continuously relevant to users, even when considering both positive and negative personal experiences on the platform, as it helps provide a sense of connectivity and authenticity in an increasingly virtual world.
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shadow-academic · 2 years
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Sorting Star Trek: The Next Generation: Part 1
I first discovered the Sorting Hat Chats through @wisteria-lodge’s excellent posts about Elim Garak and Julian Bashir, and they’ve also done a good writeup of The Original Series’s Power Trio (and Scotty), but I haven’t seen anyone do The Next Generation yet, so here I am! I intend to Sort the whole TNG cast, but that’s a lot for one post, so I’m going to split it into multiple parts. 
A more detailed break-down of the system I’m using is right here, but the basics are these:
PRIMARY (ie MOTIVE)
BADGER ~ Loyal to the group.
SNAKE ~ Loyal to yourself and your Important People.
LION ~ Subconscious Idealist. Ideals are linked to feelings and instincts.
BIRD ~ Conscious Idealist. Ideals are linked to built systems and external facts.
SECONDARY (ie METHOD)
BADGER ~ Connect with the group. Make allies, work steadily and well. Be whatever the situation calls for. If you find a locked door, knock.
SNAKE ~ Connect with the environment. Notice things. Tell people what they want to hear. If you find a locked door, get in through the window.
BIRD ~ Collect skills, knowledge, personas, useful friends. If you find a locked door, track down the key or try to pick the lock.
LION ~ Be honest, be direct, speak your truth. Either the obstacle is going down or you are. If you find a locked door, kick it in. 
Worf, Son of Mogh
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Worf is perhaps the most straightforward character in the whole show. A Klingon orphan raised on Earth (in Minsk. Minsk.) by adoptive human parents, Worf held onto his Klingon heritage by adopting a Klingon code of honor. Even when he meets other Klingons, almost none of whom take that code quite so seriously, Worf holds himself rigidly to his system, checking every choice he makes to make sure it is honorable. It’s honestly the clearest Bird primary I’ve ever seen.
Worf’s secondary is also very clear. When faced with any problem, his first instinct is to charge in, phasers blazing, mek’leth at the ready. He is unflinchingly honest in all things. He’s got one of the loudest Lion secondaries in the whole franchise.
Lieutenant Commander Data
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Bird primaries have a constructed system that they check their decisions against to determine whether something is right or wrong, whether it is constructed by them or something given to them wholesale, and I think Data’s ethical subroutines definitely count as a system that was given to him wholesale. But the ethical subroutines aren’t the whole of Data’s Bird primary. Data is constantly questioning the world around him, trying to understand what humanity is and what it means to be human. He is constantly gathering data (pun not intended) and evolving his system to account for it.
Speaking of gathering data, Data also has a Bird secondary. His knowledge is vast, and on the rare occasions that he lacks an appropriate toolset for a situation, his android brain can learn one very quickly. In short, Data is the Double Bird Spock can only dream of being.
Dr. Katherine Pulaski
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Dr. Pulaski doesn’t get nearly as much screentime as her crewmates, only lasting for one season, but I honestly really like her character. She was very obviously conceived as “female Dr. McCoy”: an older down-home Southern doctor who wears her emotions on her sleeve and is brutally honest. But does she house-match him? Well...yeah! Like McCoy, she will go out of her way to help people because they’re people. The best example of this comes in her one and only focus episode, “Unnatural Selection”. (I’m still salty about the fact that not only is Pulaski in only one season, but it’s also the shortest season due to a writer’s strike.) Captain Picard believes the risk of contagion to his crew is too great to help the crew of Darwin Station, but Pulaski refuses to abandon them, because those are people down there. So she ends up beaming one of the patients into a shuttle where the only people aboard are her and Data (because he’s immune to disease) and even though she gets infected and has to be rescued by Chief O’Brien doing some transporter technobabble, she does solve the medical mystery of the day and saves whomever she can.
Speaking of Pulaski and Data, let’s address the elephant in the room. The thing that Katherine Pulaski is most infamous for is her being an enormous dick to Data in her earliest episodes. That’s very much a Badger primary falling into the trap of dehumanization, just like McCoy with Spock, but the big difference in the dynamic is that Data is not Spock. Spock can answer McCoy’s snark with snark and it’s incredibly entertaining to watch, but Data is far too innocent and earnest for that, and it just comes across as Pulaski being mean. But what all those Pulaski-haters pointedly ignore is that Pulaski goes through some really serious character development over her limited screen time. When she gets to know Data, she stops dehumanizing him, and indeed becomes one of his biggest advocates. In the episode “Pen Pals”, when Data has the personal issue of the day, it is Pulaski who argues most fervently in favor of helping him, because Data is their crewmate, he is their friend, he is a person. Pulaski even comes to believe in Data’s personhood in ways that Data himself tends to dehumanize himself. When Data explains how he cannot feel emotions, Pulaski’s like “Really? Because your reaction back there seemed pretty emotional.” Pulaski continues challenging Data throughout her screentime, but she goes from being dismissive of him to asking Data to challenge his limits in ways he hadn’t even considered.
As to Pulaski’s secondary, she has the same uncompromising Lion that McCoy had. She is going to charge in and make sure people get the medical attention they need, and nothing, neither Captain Picard nor getting infected with a fatal illness herself, is going to stop her. (Yes, I’m bringing up “Unnatural Selection” again. It’s just the best Pulaski episode.) At the beginning of “Unnatural Selection”, Counselor Troi even straight-up calls her out as being almost too dedicated to her work as a doctor.
Dr. Beverly Crusher
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Speaking of doctors, let’s move on to the Chief Medical Officer of the Enterprise for the rest of the show. Beverly Crusher is also a Badger primary. Her priority is her patients, and her patients are anyone who is hurt. She doesn’t care about the context; she sees someone hurt, so she charges in to heal them. (That’s her Lion secondary, too.) She’s very straightforward: charge in and heal people, no matter the consequences, which can honestly cause problems, because on multiple occasions, she ends up doing something like violating the Prime Directive, which Picard then has to call her out on.
Crusher: “I couldn’t just leave them there!” Picard: “Why not?”
The fact that this exact quote is an exchange they’ve had multiple times is, I feel, very telling for both of them. Picard knows that the rules exist for a reason, but Beverly’s not gonna let a little thing like rules get in the way of helping people.
Beverly’s also doing a spot of modeling; she’s got a Badger secondary model that comes in the fact that she kind of holds the role of “everybody’s mom.” Beverly is a caring, nurturing, maternal figure not just to Wesley but to the rest of the crew as well. But it is a model; when the chips are down, Beverly’s first move is to Charge.
Captain Jean-Luc Picard
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Captain Picard is a phenomenally eloquent man. He’s downright famous for his speeches about how humanity can be better than anyone gives them credit for, about standing firm to ideals in the face of adversity, about never hesitating to do the right thing. This shows that he’s put a lot of thought into his own moral system; I don’t think a Felt primary would feel comfortable putting so much thought into examining their morals just to articulate them better. Picard sees value in the systems of Starfleet and the ideals of what Starfleet is supposed to stand for, and his Bird primary has incorporated them into his own personal system of what is right and wrong.
Like Kirk, and indeed like all Captains, Picard has a solid Lion secondary model; a natural necessity of the job is the skill to make snap decisions and judgment calls in the moment, and he’s quite good at them. But he only uses that model when it’s absolutely necessary. Picard’s preferred method of problem-solving is to trust in his crew. When faced with a problem, Picard will call a meeting of the senior staff and possibly the odd relevant specialist like O’Brien, and ask for their input on the issue at hand. What we’re seeing there is a Badger secondary leaning on the strengths of his community.
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I’ve every intention of doing the rest of the crew at a later date, but this post is already very long, and I want to do more research (read: watch more Star Trek) before I tackle the rest of them. So, to sum up:
Worf: Bird/Lion Data: Double Bird Dr. Pulaski: Badger/Lion Dr. Crusher: Badger/Lion (Badger secondary model) Picard: Bird/Badger (Lion secondary model)
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redraven3093 · 1 year
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This is not a fic??
It has no title and no plot, Its just some ideas that has been running around in my head for way to long during Exam, and I’ll be damned not to write this down and share it
 in earth there are multiple of established Hidden Yokai city spread out in the world, each city has some sort council of head and a city lord that run most of its political issues and business that run the city (a Big Mama figure if that made sense).
The important thing is, that every city has their own version of battle royale that are arraigned by the City Lords and by proxy they also have their own Champion, every 5 year the City Lords held an ultimate battle royale event where they make their Champions fight in a battle.
There was never a really an important reason as to why they held this event other than bragging rights and milking a ton of money for their own, in the Lou Jitsu (Rat Jitsu) Era, NY Hidden City had won the Battle royale plenty of times and that had truly boosted Big Mama’s power influence to become a respected City Lord among the others, but once Lou Jitsu was kidnaped and turned into a Rat, Big Mama had lost her trump card and that sucks, she still produce some good warriors and Champion to fight for her sake, but non was as good as Lou Jitsu (no one will tbh)
~But time Skips after the Kraang invasion~
The event is about to be held again this year in Japan, more specifically Tokyo’s Hidden City. Big Mama ofcourse needs to attend to as NY’s City Lord.
And also Big Mama have the responsibility to ensure that the city, both the top side and the hidden one, to be in top shape as soon as possible, for the safety of the Yokai citizen that have a living in the Top Side city and for upholding her reputation as the City Lord.
She became one of the top donators for the reconstruction of New York city.  
(I will make Big Mama lose as much as money as I want and pays for everything that is needed until the day comes where the writers make her actually pays for the shit she pulled in S2)
Quiz Time! guess who is Big Mama’s current Battle Nexus Champion??
Leon, Its Leon.
(Consequences will finally bit this blue clad reptilian in the ass)
By rule, Big Mama have to bring her Current Champion to fight in the event, and Leon’s name is put in front and center on the Battle Nexus data base as Big Mama’s newest top dog and Champion.
Big Mama, Leon and Splinter are not thrilled for this, Splinter almost lost his son not to long ago and he’d be damned if he let him fight again, he knows the event isn’t an easy thing, so he forbids Leon to participate in the Event.
Big Mama wouldn’t be a City Lord if she can’t manipulate her way to get what she wants, convincing Splinter was not essential (though it would certainly help) but she knows that the one that is important to be convinced was Leon himself, and Leon knows this too.
So, two manipulative rat bastards are now having a deal discussion for Leon’s participance in the event, if being honest the curiosity of being in another Yokai City is what draws him in the most, but Leon manages to wring in some good payment for his participation even if he didn’t win the event.
       “Just give them a good show my little blueyboo, I’m sure you’ll find yourself in a joyous bumblely timey time” She cheerfully says
And so, a contract was made between Leon Big Mama and Splinter knows that one way or another, his blue clad son will definitely participate in the event once he shows even an ounce of interest, so he assigned Donnie to accompany and keep a watch on him. (a questionably BAD choice)
Mikey ask for pictures or souvenirs from their trip and Raph ask Donnie to be generous and pretty please share their collective brain cell this time because he didn’t want Leon be dumb and cocky and made a bad moves in the arena.
Leon was offended by that, and Donnie hoarded the Brain Cell even harder.
this will have part 2
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How to Become a Data Analyst in 2022?-
In the past decade, data has become of prime importance. Organizations are investing heavily to ensure the maximum yield universalize of information from the firm’s database. The need for this extract has risen after the revolution in trade brought about by data analytics. Data Analytics has revolutionized the way the higher management or the owner of the business see’s the data. The insights gained post evaluation and analysis of data and showcasing the same in a visually appealing format or report have modified the approach to business and the campaigns that the firms run to push sales and improve the goodwill of the brand.
How to become a Data Analyst With No Experience?
Data Analytics is a path of untold possibilities and is expected to grow larger than ever before. Since the revolution of digitization of records has lowered the operating costs for companies. The digitized data is stored in huge data silos called databases either through an outsourced connection or through cloud servers whichever fits the need of the business or startup. Data Analytics helps in gaining insights that might be hidden inside the data.
The future of data analytics, in general, is democratization. We have come a long way from only the statisticians or only the number crunchers being able to work with data and then hand it over to the analysts. The term that has been buzzing around the conference rooms is self-service data analytics. Being able to answer the questions of our customers which they don’t even know makes it easily achievable by employing tools like Power BI & Tableau which make it accessible to anybody. These tools do a great job of integrating and implementing a lot of features that require no coding.
Real-time decision-making based on real-time data becomes possible by taking or utilizing some of these advanced data analytics tools which help the user to create a connection between artificial intelligence and machine learning. Data analytics enables the operators to take those complex problems/issues and break them down for business users to understand whilst keeping it simple. The way Power BI & Tableau can drive insights from any basic data set extracted from any database.
Everything around us is data and we just need ways to harness, understand, learn and make good choices based on data analytics. It is here to stay and the next big wave is how do we implement it so it stays forever and continues to expand.
A Step-by-Step Guide to Become a Data Analytic:-There are basic steps with which anyone can start a career as a Data Analyst: –
Get a bachelor’s degree in Math or Computer science with priority on statistical or analytical skills.
How to become a data analyst without a degree – The easiest way to do this is to master important data analytical skills.
opt for a certification course with Analytics Training Hub to start a data analyst learning path.
Get a job at an entry-level as a data analyst.
Earn a Master’s in Data Analytics.
What does a Data Analyst do?
The job profile of a data analyst entails multiple steps, starting from: –
Discover the problem or determine what the owner needs.
Do they need a dashboard, do they need reports, do they need to do some type of analysis on their product and give some type of recommendation?
When the analysts finally get the idea of what they need to do, they have to create a plan of action.
As to when will the user be getting this data and where is it coming from.
Often it can be the user’s job to communicate that to the team.
The next thing that the user would want to do is to collect the data.
Data can come from a ton of different sources so whether that is an SQL backup, a flat file, or an API.
After extraction, the analyst should be able to get all that data into one place.
Then as a user, you would need to work with your programmers to create an extract, transform and load (ETL) process.
So, the user is going to work with the programmer to get the data, and then both the user and the coder are going to create business rules to transform it for how the data analyst wants it to look in your system.
Then the operator loads the data and this can also be known as creating an ETL pipeline.
if you have data that’s going to be coming in either weekly or monthly the operator wouldn’t want to repeat this process manually every single time.
So, creating a pipeline is creating an automated process to bring that data, in the same way, every single time and that’s going to save you a lot of time.
The very last thing is aggregating your data which just means standardizing data and putting it all together instead of having it as separate sources.
the next step would be to clean the data  Data is always messy.
Sometimes they use three different date formats, people’s names are capitalized for absolutely no reason and sometimes somebody forgets to add the customer id. So, you can’t map the patient in your system.
The analyst needs to do all this because it makes the data a lot more usable for later processes and part of this is normalizing and standardizing the data so that when you do your visualizations or your reports later all the data looks the same that can be used in any part that you need to be used in.
The next thing that the user needs to do is set up the data for reports and visualizations and oftentimes the user achieves this is by creating views.
A view allows the operator to combine several tables into one and then choose a subset of that. A data that the user wants to use for the reports and visualizations and each view may need to be formatted differently based on what the operator is going to be using it for in the report or the visualization.
Last and foremost is creating the reports and along with automation of that process so that if the owner wants it every week or every month it can just generate the report from a stored procedure or a job that automatically sends it out with the latest data every week or month.
The user can also connect that data to a data visualization tool like Tableau, power bi, python, or R.
What is the future Data Analyst job?
As per leading data connoisseurs of the data industry, the job profile of a data analyst seems to hold an extremely promising prospect in the next coming decade or two. The data Analyst job is a stepping stone and may lead to many of the below-mentioned job profiles depending on your interests: –
Data engineers:
data engineer would create the platform and the data structure within which all the data from the users would be captured for example what items they buy that is in their cart currently and what is on their wish list they have to make sure that the captured data is stored in such a fashion that is not only well-organized but it’s also easily retrievable. They should be comfortable working with every data source and employ ETL queries to collate data from multiple data sources and then organize all of this data in data warehouses or databases so that colleagues in the company can make the best use of it. To become a data engineer you need to acquire knowledge of languages such as Python, Java, SQL, Hadoop, Spark, Ruby, and C++. Now all of these are not mandatory but they vary from company to company for the job profile of a data engineer.
Business Analysts:
Business analysts are expected to draw insights from the data which would directly impact business decisions. Business analysts are directly involved in day-to-day business activities and there are a lot of ad hoc analyses that business analyst is expected to do, for example in an e-commerce company a business analyst would help the marketing team identify the customer segments that require marketing or the best time to market a certain product or why the last marketing campaign failed and what to do in future to prevent such mistakes hence for a business analyst a good understanding of business data and statistics is essential.
The tools and languages that would be most commonly used by you as a business analyst would be Excel, SQL, power bi, and tableau. Job profile of a business analyst may also be known as a data visualizer or a business intelligence professional who’s are responsible for creating weekly dashboards to inform the management about weekly sales of different products, the average delivery time, or the number of daily cancellations of orders, etc.
Data scientists:
A data scientist is a rare gem that employs data that has been existing in the organization to design business-oriented machine learning models. As a starting point, a data scientist can go through the available data of the company to look at various buying patterns identify similar items on the website, and then create algorithms around the same so that the website can automatically endorse products to the users based on the navigation history purchase of the consumer. Now this solution has to be effective enough that it can predict future purchases in real-time for visitors of the website.
Data analysts are expected to perform a lot of unplanned analyses which can facilitate decision-making within an organization. Data scientists on the other hand not only perform ad hoc analysis and create prototypes but also create data products that make intelligent decisions by themselves and this is where machine learning becomes extremely critical. For example, the suggestion you get after you buy a particular item or based on the items that you have on your wish list are because of machine learning models built by a data scientist.
The requisite skill for a data scientist is knowledge of algorithms, statistics, mathematics, machine learning, and programming languages such as Python, C, etc. They should also have an understanding of trade and the aptitude to frame the right questions to ask and find the answers from the available data. Finally, a data scientist should be able to communicate the outcomes efficiently to the team members and all the involved stakeholders.
Salary of a Data Analyst:
The salary for a Data Analyst may differ in different organizations. But, a Senior Data Analyst with the right skill and software knowledge may command a high price for the services offered.
The average salary for an entry-level Data Analyst may start from INR 2.9 lakhs per annum.
The average salary for a mid-level Data Analyst may start from INR 4.5 lakhs per annum.
The average salary for a Senior level Data Analyst may start from INR 9.5 lakhs per annum.
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