What makes statistics different than mathematics

[SgtHughGRection]

Lmao the different clothing for him imitating the student killed me

[iRedee]

Easily one of the best video on the internet... Thanks man...

[khaliaf]

Incredible explanation. I only hope that going forward I will come across many educators like you.

[trishakanyamarala]

This is most informative video I have ever seen on YouTube. The level of explanation is crystal-clear.

[truthful]

Good video. Talks about the philosophy of statistics and delves into the meaning behind each chapter.

[paulinha]

Thank you so much for this video. I've been passionated for stats since my first class on it, but I often question myself if I should keep pursuing this major giving my dificulteis with math. I’m definitely not the quickest with numbers but I do get the concepts. I also have a hard time memorizing facts but on the other hand I have a strong logic, so I am usually able to draw conclusions if I have time for it. It’s challenging because I see most of my classmates looking at problems and solving them within seconds and I take so long. Anyway, your explanation between the subjects is very encouraging. I’ve always loved philosophy, psychology, anthropology, and I feel like stats is the tool to put all these subjects together to better understand the world and our society so, thanks again for the encouragement.

[a_imalik]

Your students are lucky! Thank you for explaining this so well 🤗

[dipankarbanerjee]

This is epic and wonderful!! Like unimaginable and well explained!! I wish to see more like this video!

Love ❤ from India sir.

[seth]

I am really glad I came here to understand the difference between statistics and math. The internet is filled with answers that are like the first example you used and it's nice to know it's not so simple. I am a freshman undergraduate looking at both a math and statistics major. I really like how applicable statistics is to the real world. Not that you said mathematics isn't. But maybe just not in the ways that I am looking for.

[michaeljagdharry]

"Rather than compare the two..."

-subtly includes 'fun with a thriving job market' on the stats side of the board xD

[ganeshshetty]

I wish I had professors like you while learning these subjects!

[nolanfontaine]

Service is the heart of statistics. I love that! It really gives me my WHY when confronted with the HOWS.

[jadeorchid]

I have never seen anyone on YT explain subjects so well . Also, thank you millions for not playing music in the background

[frunkybooii]

Brilliant educator. Concise, informative, and passionate, thank you

[nmc]

Thank you Dr. Crawford for your wonderful explanation. I especially enjoyed your breakdown of an intro stats class into math and statistical concepts. Could you please recommend an intro textbook that adequately addresses the topics you listed under statistics? Keep making videos! You are saving the world!

[starostadavid]

So good. Students should watch it in the beginning, being kind of confused, and then at the end of semester so they can click with a concept more. It's really good put together.

[gabriell]

This guy is extraordinarily good at explaining things. He makes it look so simple!

[peteryueqiren]

Man this is the best explanation I have ever seen. Thanks for sharing!

[swavekbu]

Excellent video! The fact that students who approach stats as if it were a math class do poorly is testimony to the way math is too often taught, which is sadly in a step-by-step algorithmic computational fashion, or at least that's how many students try to get through it. Instead, they should see math as rigorized thinking and precise expression of relevant philosophical concepts such as form, pattern, distance, closeness, continuity, etc. The "step by step procedures" in textbooks is partly responsible for this. So they learn to manipulate formulas, etc., using this approach, pass the course, then get to stats and think they can do the same to succeed. But that kind of thinking doesn't work in stats (assuming the course is taught well), because of all the reasons Scott mentions. Stats, when combined with research and science, requires many inputs to reasoning through a problem, and in scientific applications, it can prove very difficult figuring out optimal designs and appropriate analyses. Not only can it be difficult verifying assumptions, etc., but even determining whether your variables are best measured on a pseudo continuous scale or categorical can be very difficult. And, even once you've conducted your analyses and answered your hypotheses, determining what you can vs. cannot conclude scientifically can be very challenging. Most students greatly overestimate what can be concluded from a statistical model. What is usually more relevant to drawing strong scientific conclusions is the underlying research design. As Scott discusses, it's never as simple as simply running a statistical test. When you're working with statistics, you're usually working with science at the same time, and all the things Scott mentions has to be considered in your decision-making and in drawing conclusions from your analytical method. You have to be well-versed in the field in which you are applying the statistics so you know the types of conclusions that can vs. cannot be drawn on a substantive level.

[indrajit]

Fantastic explanation. Superb editing. Transition shots taken so meticulously that the edit does not seem jump cut (except few places). The video making helps the topic to be more interesting. Thanks for the video!