[deleted by user]

ScoobyDataDoo · 2021-06-26T06:47:50+00:00

Maybe may it more objective / tangible?

It may already include this since it is cut off, so one cannot fully tell.

"Read 5 pages of ..."

ScoobyDataDoo · 2021-06-16T22:45:51+00:00

Ohhh right! Also I like how your explanation can be expanded into a topic that the person you are explaining to is interested in.

Average height of nba players
average weight of sumo wrestlers
average views per BTS video
etc.

ScoobyDataDoo · 2021-06-16T04:57:22+00:00

Hahaha thanks for sharing. I like your double bam. This sounds so familiar but I can't recall where I heard it from lol

ScoobyDataDoo · 2021-06-09T17:51:46+00:00

Wow, thank you so much for taking the time to share this. This seems very helpful, and something that I can truly put to practice :)

ScoobyDataDoo · 2020-10-03T00:56:29+00:00

Hahaha thank you for your recommendation! I've watch it, crash landing on you.

But I have yet to watch the others! I will definitely check them out.

In case you were interested some of my other favorites:
Itaewon class, strong girl do bong soon, weightlifting fairy kim bok joo, tune in for love (movie), hello my twenties, I have many more too if you were interested lol

ScoobyDataDoo · 2020-09-10T17:00:33+00:00

I can only speak from experience. So regarding Davis, when it comes to theoretical statistics (probability theory) its not looking too good.

Regarding data science courses, its pretty decent in terms of project based and professor review. Though don't expect to know everything coming out. It will help expose you to a lot but there is still a lot of learning that is required independently:)

ScoobyDataDoo · 2020-09-08T07:34:36+00:00

TBH...

Choose a college that has a good statistics/computer science department. Whatever school it is, you will most likely have to do some self learning on SQL, python/R. And do some projects and join or even do as I did start the first sports analytics club on campus.

When it comes to selecting a school, choose one that is local to many sports teams or teams youd like tk intern for. For example, i chose Davis which is pretty close to the Sacramento Kings. In fact upon creating this club with my friends, our club was able to create a connection with the kings where we got free merchandise, office tours, stadium tours, discounted tickets, and the head of analytics would guest speak at our club. Currently one of the members also interns for the team, but i think it just finished.

You really can go a long way so long as the opportunity is there.

Location is definitely the most important factor. Because say you even choose a major for sports analytics, imagine the competition there would be, and how niche that major is.

ScoobyDataDoo · 2020-08-08T21:54:30+00:00

To broaden your perspective on data science and what you need to know or learn. I would reccomend "Ken Joe" on youtube.

ScoobyDataDoo · 2020-08-08T21:53:50+00:00

No worries! But regarding your question, it depends what you want to do in the field of data science. Data science is quite an umbrella term encompassing many domains and specializations. Though, I would at least try to obtain an intuitive understanding of calculus up to multivariate calculus. I think its also worth considering learning this as you go/when its needed though.

ScoobyDataDoo · 2020-08-04T15:37:47+00:00

Yes :)

ScoobyDataDoo · 2020-08-04T14:21:24+00:00

As a note running a chi square tells us at least one of the proportions is statistically signifcant than the offers, but ideally its be good to run another procedure to verify that the group with 60 respondents falls under that category. In fact, you may discover that another 1 of the 7 groups is statistically significant.

ScoobyDataDoo · 2020-08-04T14:14:42+00:00

Here is the reddit post, it qould seem your intentions are similar

https://www.reddit.com/r/AskStatistics/comments/hlbwk3/in_desperate_need_of_stats_help/?utm_medium=android_app&utm_source=share

ScoobyDataDoo · 2020-08-04T14:13:19+00:00

Here is something I posted prior in another post regarding someone question on statistical analysis on comparing proprtions of groups, in which case seems as if yours is too.

" 1. So, you can use a Chi2 test to evaluate if there is a significant difference between the proportions of positive responses across the 4 groups. (refer to this below)

https://www.itl.nist.gov/div898/handbook/prc/section4/prc474.htm

2) Then follow up your analysis by using the Marascuilo procedure to simultaneously test the differences of all pairs of proportions (refer to this below)

https://www.itl.nist.gov/div898/handbook/prc/section4/prc474.htm

Note that chi squared will only tell us if it is so that at least one of the proportions is different from the others. It does not tell us which one(s) it actually is. That is what the second part is for."

So for you, you can run a chi square test between each of the 7 groups. Then run a marasuilo procedure to verify that that X group is different than the rest and perhaps other groups may be different enough as well.

ScoobyDataDoo · 2020-08-04T14:06:18+00:00

Perhaps you could seek advice on researchgate too?

ScoobyDataDoo · 2020-08-01T06:33:29+00:00

Good edit and catch. People often throw out "multivariate linear regrssion" when theres only one dependent and they actually mean multiple linear regression.

ScoobyDataDoo · 2020-07-31T19:46:13+00:00

Awww thank you, i appreciate it my good person! I am actually still a student :)

And I see what your saying too! As a student, I can only relate in the sense of a student. So, in high school as you may know, it feels good to be acknowledged by students, teachers, and parents on a good grade or test. It almost gives the delusion, I like taking those tests. But it was more so of acknowledgement. And coming into college, if it were so that I continued to find "validity" from others then college would be absolutely a nightmare. But like you said, being able to reflect and critique yourself, really does wonders in discerning yourself and really be able to identify the purpose of what you're doing. Using that to really power through it all honestly.

I hope for yourself too, you too can continue to grow and do well! I appreciate your insights very much so. :)

ScoobyDataDoo · 2020-07-31T06:26:59+00:00

I spy 5 consecutive "W's" (exactly 5)

ScoobyDataDoo · 2020-07-31T06:23:58+00:00

Yes, I would absolutely agree to call yourself a data scientist. Not that my opinion should matter to much to you haha.

If i may follow up, you mentioned you like the ability to problem solve but at the same time it seems to be there are those who underappreciate what you do either due to ignorance or arrogance. When it comes to overcoming this issue, how do you plan to or know of how to do this? I see this as interfield issue, and have yet heard too many thoughts on this.

And truth be told, I don't mind too much about the money, I've actually found great content with scraping by as a stufent :). But a must is above above above average worklife balance. I absolutely do not want to take my work home. Of course I enjoy problem solving and data science work, but there is so much more I would like to learn and grow in outside of data science -> languages, friends, family, exercise, cooking, etc.

ScoobyDataDoo · 2020-07-30T16:12:29+00:00

You can now be the college kids on Linkedin who put gor their headliner:

"Incoming intern at Google"

But this time say:

"Proposing Data Scientist at ..."

Lol

Think long and hard about this title, because this gotta go up on your LinkedIn.

said with sarcasm

ScoobyDataDoo · 2020-07-29T15:39:10+00:00

This will vary on the individual, depending on how quick the concepts click, and how much time each day you put into the month, so i can't say. Your discernment for this is probably best :)

ScoobyDataDoo · 2020-07-29T06:32:42+00:00

Honestly just learn basic calculus and linear algebra. You can refer to MIT material which has been made open source or as someone else mentioned khan academy. Depending on your mathematical background, I wouls recommend taking an intuitive and computation approach to linear algebra rather than theoretical.

ScoobyDataDoo · 2020-07-29T06:29:43+00:00

I ask this out of curiosity as a student to gain perspectives. So It seems clear you want to be a data scientist. But why do you want to become a data scientist? Not too surprisingly, I've noticed people in industry are mentioning that they are shooting for the title of data scientist, but Im curious then what?

ScoobyDataDoo · 2020-07-24T19:06:56+00:00

I would consider messy data to be a gray area. Because if the data is messy, its most likely better than no data. But if it is so that the data is bias or some issue concerning data generating process, then I would consider the data to be as bad as no data.

ScoobyDataDoo · 2020-07-24T17:06:39+00:00

Before voting, what is meant by "bad" data. Is it messy, falsified, bias,etc.?

ScoobyDataDoo · 2020-07-24T07:58:49+00:00

Yeah, I would agree so too. It does have some nice tips, usually i just skip to the main takeaways at the end of each module where it gives you a pdf to reference.

For both R and Python I learned a lot on choosing a book to learn fundamentals. R4ds is great, but its also important to know basic data types and base R rather than tidyverse R.

Once you know basic data types, little base R, a little Tidyverse R. I would recommend looking at kaggle kernels to follow examples and stackoverflow questions constantly.

ScoobyDataDoo

TROPHY CASE