# What Is Statistics: Crash Course Statistics #1

Hi, I’m Adriene Hill, and this is Crash

Course Statistics. Welcome to a world of probabilities, paradoxes

and p-values. There will be games. And thought experiments. And coin flipping. A lot of coin flipping. Statisticians love to talk about coin flipping. By the time we finish the course, you’ll

know why we use statistics. And how. And what questions you ought to be asking

when you run across statistics in the world. Which is ALL THE TIME. Statistics can help you make a guess whether

or not you’re going to be accepted to Harvard. Marketers use them to sell us gold-lame pants. Netflix uses stats to predict what show we

might want to watch next. You use statistics when you look at the weather forecast and decide what to wear–dress or jeans. Policy makers use them to decide whether or

not to invest in more early childhood education, whether or not to spend more on mental health

services. Statistics is all about making sense of data–and figuring out how to put that information to use. Today, we’re going to answer the question

“What IS Statistics?” INTRO The legend says that during a late 1920’s

English tea at Cambridge, a woman claimed that a cup of tea with milk added last tasted different than tea where the milk was added first. The brilliant minds of the day immediately

began to think of ways to test her claim. They organized eight cups of tea in all sorts

of patterns to see if she really could tell the difference between the milk first and

tea first cups. But even after they had seen her guesses,

how could they really decide? Because, she’d get about half the cups right

just by randomly guessing either milk or tea. And even if she really could tell the difference,

it’s completely possible that she would miss a cup or two. So how could you tell if this woman was actually

a tea-savant? What is the line between lucky tea guesser

and tea supertaster? As fate would have it, future super-statistician

and part time potato scientist Ronald A. Fisher was in attendance. During his lifetime, Fisher began work that

set the stage for a large portion of Statistics which is the focus of this series. These statistics can help us make decisions in uncertain situations, tea-taste-tests and beyond. Fisher’s insights into experimental design

helped turn statistics into its own scientific discipline. And, although Fisher didn’t publish results

of this tea-test…the story has it…the woman sorted all the tea cups correctly. Just in case you were curious. At this point, it’s worth mentioning that

there are two related–but separate–meanings of the word statistics. We can refer to the field of statistics…

which is the study and practice of collecting and analyzing data. And we can talk about statistics as in facts

about… or summaries… of data. To answer the question “What is statistics?”,

we should first… …ask the question “What can statistics

do?” Let’s say you wake up at your desk after a

long evening studying for finals with a cheeseburger wrapper stuck to your face. And you wonder… “why do I eat this stuff? Is fast food controlling my life?” But then you tell yourself, “No. It’s just super convenient..” But you’re worried, you’re thinking about

how great it is that McDonald’s serves breakfast all day RIGHT NOW. But maybe that’s normal, finals are this week

afterall, so you google the question “Fast Food consumption” and you find the results

of a fast food survey. The first thing you might do is start asking

questions that interest you. For example, you could ask, Why do people

eat fast food? Do people eat more fast food on the weekend

than on weekdays? Does eating fast food stress me out? Now that we have some interesting questions,

we need to ask ourselves an even more important one: Can these questions be answered by statistics? Like I mentioned earlier, statistics are tools

for us to use, but they can’t do all the heavy lifting. To answer the question about why people eat

fast food, you can ask them to fill out a questionnaire, but you can’t know whether

their answers truly represent what they’re thinking. Maybe they answer dishonestly because they

don’t want to admit that they scarf McDonalds because they’re too tired to cook dinner,

or because they are ashamed to admit they think Del Taco is delicious, or because none

of the given answers represented their reasons, or they may not really know why they eat fast

food. Armed with the results of the survey, you

could tell you that the most common reason that people reported eating fast food was

convenience, or that the average number of meals they eat out each week is five. But you’re not truly measuring why people

eat so much fast food. You’re measuring what we call a “proxy”,

something that is related to what we want to measure, but isn’t exactly what we want

to measure. To answer whether people eat more fast food

on the weekends, or whether eating it more than twice a week increases stress, we’d

not only need to know how much people are eating fast food, which our questionnaire

asked, but also which days they eat it. And we’d need an additional measure of “stress”. You can use statistics to give a good answer

about whether you’re going through the drive-thru more on the weekend, but even the question

of whether eating fast food is associated with higher levels of stress is hard to answer

directly. What is stress and how can we measure it? And are people eating fast food because they

are stressed? Or does eating all those calories make them

stressed? It’s often the case that some of the most

interesting questions are the ones that can’t be directly answered by statistics–like why

people eat fast food. Instead we find questions that we can answer–

like whether people who eat fast food often work more than eighty hours a week. The tools we use to answer these questions

are statistics-plural–and there are two main types: Descriptive and Inferential. Descriptive statistics, well… they describe

what the data show! Descriptive statistics usually include things

like where the middle of the data is–what statisticians call measures of central tendency–and

measures of how spread out the data are. They take huge amounts of information that

may not make much intuitive sense to us, and compress and summarize them to …hopefully…

give us more useful information. Let’s go to the the Thought Bubble. You’ve been working for two years in the

local waffle factory. Day in and day out, you create the golden-browny-iest,

tastiest frozen waffles ever created. The holes are perfectly spaced. Screaming for syrup. And now you want a raise. You deserve a raise. No one can make a waffle as well as you can. But how much do you ask for? An extra thousand dollars? An extra 5-thousand dollars? You know you’re valuable, but have no idea

what other waffle makers get paid. So you dig around online and find there’s

an entire subreddit devoted to waffle makers. And someone username “waffleleaks” has

posted a spreadsheet of waffle maker salaries. Now with a quick glance at this huge list

of numbers, you can see whether the woman who works a similar job at the rival frozen

waffle company makes more than you. You can see how much more you are making than

the new guy, who’s just now learning to mix batter. But you still don’t know much about the

paychecks of your waffle company as a whole. Or the industry. Cause it turns out there are thousands of

waffle makers out there. And all you see is a list with data points,

not patterns that can help you learn more about how much you might be able to convince

the boss to pay you. Here is where descriptive statistics come

in. You could calculate the average salary at

your company as well as how spread out everyone’s salaries are around that average. You’d be able to see whether the CEOs’

paychecks are relatively close to the entry-level batter makers, or incredibly far away. And how your salary compares to both of their

salaries. You could calculate the average salary of

everyone in the industry with your job title. And see the high and low end of that pay. And then, armed with those descriptive statistics,

you could confidently walk into the waffle bosses office and demand to be paid for your

talents. Thanks, Thought Bubble. While descriptive statistics can be great,

they only tell us the basics. Inferential statistics allows us to make….inferences. (Clever namers, those statisticians.) Inferential statistics allow us to make conclusions

that extend beyond the data we have in hand. Imagine you have a candy barrel full of salt

water taffy. Some pink, some white, some yellow. If you wanted to know how many of each color

you have, you could count them. One by one by one. That’d give you a set of descriptive statistics. But who has time for all that? Or, you could grab a giant handful of taffy,

and count just those you have pulled out, which would be using descriptive statics. If your candy was, in fact, mixed pretty evenly

throughout the barrel, and you got a big enough handful, you could use inferential statistics

on that “sample” to estimate the content of the entire taffy stash. We ask inferential statistics to do all sorts

of much more complicated work for us. Inferential statistics let us test an idea

or a hypothesis. Like answering whether people in the US under

the age of 30 eat more fast food than people over 30. We don’t survey EVERY person to answer that

question. Let’s say someone tells you that their new

brain vitamin–Smartie-vite–improves your IQ. Do you rush out and buy it? What if they told you that the average IQ

increase for Group A– twenty people who took Smartie-vite for a month–was two IQ points,

and the average IQ increase for Group B–twenty people who took nothing–was one IQ point. How about now? Still not sure? It is a pretty small difference right]? Inferential statistics give you the ability

to test how likely it is that the two populations we sampled actually have different IQ increases. However, it’s up to you, as an individual,

to decide whether that’s convincing or not. And don’t be alarmed if the bar you set

isn’t the same in every situation. It’s entirely okay to have different standards

for the questions “does my cat like Fancy Feast more than Meow Mix?” vs “does this

drug cure lung cancer?”. It might take more evidence to convince you

to take a new supposedly cancer curing drug than to switch cat food brands. It should take more evidence to convince you

to take a new supposedly cancer curing drug than to switch cat food brands. With inferential tests, there will always

be some degree of uncertainty since it can only tell you how likely something is or is

not. Your job is is to take that information and

use it to make a decision *despite* that uncertainty. If Statistics were a superhero, it’s batcall

would be uncertainty, and it’s tagline would be “When you don’t know for sure, but

doing nothing isn’t an option.” Statistics are tools. Statistics help us make sense of the vast

amount of information in the world. Just like our eyes and ears filter out unnecessary

stimuli to just give us the best, most useful stuff, statistics help us filter the loads

of data that come at us everyday. Descriptive statistics make` the data we get

more digestible, even though we lose information about individual data points. Inferential statistics can help us make decisions

about data when there’s uncertainty (like whether Smartie-vite actually will increase

your IQ). But statistics can’t do all of the work. They’re here to help us reason, not to reason

for us. They help us see through uncertainty, but

they don’t get rid of that uncertainty. To push our tool analogy a step further. Statistics, like chainsaws , are pretty useless even dangerous without understanding how they work. We need to know how to use them and how not

to use them. As we will see in later episodes, statistics

done poorly can lead us to some pretty silly conclusions. And, chain sawing done poorly leads to about

36-thousand injuries in the US each year. 81% of which are lacerations. Did you know that almost no one dies because of chainsaw injuries? Once in a while, but it’s very rare. 95% of the people who are hurt by chain saws

are male. This does NOT necessarily tell us that males

are significantly worse chain sawers. Statistics can help us plan a vacation to

Bali in December. They can help us optimize our chances of winning

our fantasy football league. They can help us budget our meal card at college. Statistics can help us decide whether that

additional insurance the guy at Best Buy is trying to sell us on our new blender is worth

it. Statistics can also help us decide whether

or not to go ahead with an invasive heart surgery. Statistics can help NGOs optimize the amount

of food aid they send to refugee camps. They can help policymakers decide if they

should spend more or less money on helping students pay back their school loans. And can help you decide how much money you

should be comfortable borrowing for college in the first place. There is a lot statistics can help us with

but some things statistics can’t do.Thinking statistically means knowing the difference. So, when your brother says he used statistics

to prove that your mom loves him more you can rest easy knowing the only question he

answered is whether she gives him slightly more ice cream each night. And you’ve got data suggesting she gives

you extra sprinkles. Thanks for watching. I’ll see you next time.

Beautiful!

Who else is starting a statistics class in uni?🙋🏽♀️

Finally, video that the teacher talk slow

Teaching stats for the first time this year to high school students. This video is very helpful and I will be using it on the first day 🙂 Thank you.

I Whant graph note bar graph

God damn Chad and Stacy's are ruining EVERYTHING

Or what lies they should be telling them

a song by ya boi lil timmy tim (timothée chalamet)

ΣΕΠΤΕΜΒΡΗ ΚΑΛΗΣΠΕΡΑ

Did you rehearse a thing your saying? it's like incredibly difficult to hold eye contact with you while your rumbling off. For peat sake! take what your saying more serious and talk to me not at me in 5 different locations. Thank you!

I was expecting John Green 😂

There was a statistician who slept with her head in the freezer and her feet in the oven. When they asked her how it felt, she said, "On average, the temperature is just right."

got hungry watching this video

Excellent! I would like to recommend that viewers read Chance: A Guide to Gambling, Love, the Stock Market, and Just About Everything Else by Amir D. Aczel and books by John Allen Paulos (even Irreligion makes reference to mathematics).

can you do a series on the fallacies?

Did the waffle lady ever get her raise?

Great start!!

Digital Statistics = data science

The way this video is edited makes it feel a bit haphazard. I found it difficult to follow because of that.

amazing .. thank u for this video … i'm studying statistic but i want to lean more about statistic

Very good, thank you

is this video on statistics or on fast food

Chainsaws are sexist

I want that room setup!

Remember these questions:

What

Where

When

Why

and How

TEA TEST

Something significant I learned from this video: Best Buy sells blenders 😮

More hand movements , more MORE!!!

There's more than one T in statistics

3:14 Ruso-English keyboard

I guess you guys easy to get it

,If ask to little timytim

That studio is awesome

why isn't this channel on the crashcourse website?

You need cage free, range fed vitamins.

I just read three books on statistics and this video just reinforced everything with these delightful animations. God bless you guys.

thank u, I will try not to fall asleep this time, will keep trying to watch video without doing so lol !!!

Balo

1:50, where you pour, how you pour. Fluid density seperation, mixology, versus homogeneous entrainment.

Thank you ❤️

You love food so much!!!!

This just isn't helping.

oof I have to take this in 12th grade next year…

I love this crash course.

One note is that there are to many repetitions about why statistics are useful

To much gargin get to the freaking point !!!!!

I was thinking about the same example she gave (McD 2:50 ) is it statistics or pure luck? is this a coincidence ?

why my statistics lecturer didn't explain as interesting as this!

shouldn't it be "what ARE statistics?" I guess I need to watch crash course on grammar.

The guy who made such a survey on fast foods instead of studying is a genuine master level procrastinator.

Hail sir!

Without a basic understanding of statistics, double-entry accounting, and logic, you are going to stumble through life as a blithering, gullible idiot ripe for exploiting.

And that's how I decide which video to comment on.

Which is more likely? That election poll results were wrong (a failure of statistics) or that Russia meddled with the election and changed the outcome?

you are amazing

I LOVE THIS SM. I have always loved crash course; mainly because of my love for history, literature, and science, but I have never been very good at my stats class because I have never been good at math, now one of my favorite youtube channels allows me to improve!! I am very thankful for this series 🙂

Would you rush out and buy it?

yesGroup A had an avg increase of 2 IQ points, Group B was 1. How about now?

hEck yeswow!!! never knew statistics was this interesting and useful. when i chose statistics as one of my subjects for AS level, i really wasn't looking forward to it. i just chose it because it "looked easy" to me plus it was a perfect combination for my business course but then i realized that it's all concerning probability so i gave up trying cause i really hate probability. now though, i have a new hope, i have the feeling that i didnt make any mistake by choosing this course, thanks for enlightening me. i really love it now. i still wish though that i had you as my teacher.

just beautiful, thank you!

I’m taking Integrated math 3 and last semester I got a 4.7 should I take AP Statistics? Please answer ASAP

For someone so intelligent about stats, you sure do have a poor grasp of English. Also, based on one of your other vids, you're clearly a liberal. So, screw off.

I love these crash course series. sometimes I feel just a general overview of knowledge would suffice for my application and this is a great way to get it!

The description of inferential statistics is phenomenal- perfect for my 9th grade bio students. Thank you!

Statistics was said 93 times in this video.

I hate statistics why do so many women like this subject. ??

This is simply amazing. I’m just a high school student who was interested in what Statistics really was and you have done an astonishing job teaching us about it. I am looking forward to the rest of the series, and be sure to like all her videos!

Mean, median, mode….

AP Stats is easier than Honors PreCalc

I am only learning about statistics and I’m looking forward to this statistic series. ITS SO FUN AND COOL!!

A very lucid explanation!!!

except the mongols! I love crash course 🙂

So hard i can't answer it

If your mom gives you ice cream every night, she doesn't love you. She's fast-tracking you to diabetes. She H A T E S you.

I'm a stan for chainsaw statistics! Please feed me more.

So many things behind the scene to conclude an answer.

I so love this video 😍 The way the ideas were arranged was so amazing 😉 Very helpful for my class in statistics.

The background !! So ingenious ! The bell graph , the pie chart , the candle graphs… So aesthetically pleasing..😍

who's here for the AP 2019 stats test?

who else hates statistics?

Thanking you very nice teaching

Incredible introductory lesson

IS THIS REALLY A QUESTION…..MORONS

why am i finding this just after my psych ia

check the statestecks

Great insight into basic statistics but please check your spelling on 9:51 “…ITS batcall would be uncertainty, and ITS tagline…”. Other than that, I love your videos!! 🙂

This video has left all the important questions unanswered: did the waffle girl get the raise? how many taffies did you eat? and most importantly, does the cat like your cat food?

Does this whole episode have to be about food? And junk food at that. Now I just want a burger, waffles and candy

I highly doubt it’s bad usage that causes injuries. Logging is just deadly even for the experienced expert.

In case you were wondering the origin of the word "statistics" (courtesy Wiktionary):

From German Statistik, from New Latin statisticum (“of the state”) and Italian statista (“statesman, politician”). Statistik introduced by Gottfried Achenwall (1749), originally designated the analysis of data about the state.

What ARE statistics….if you cannot tell the difference between one and more than one, you are not fit to comment on anything to do with math.

I loved this video! Great job. Thank you!

Are there any other anxiety-ridden over-thinkers wondering if statistics would be right for them? Or should take a course for the hell of it? Lol constantly over-thinking and feel like this would help me try to make sense of the world around me in a way.

Is course is easy or tough vs physics

I am the only one who paused the intro and read what they try to write?

Globally, there are approximately 1.5 billion domestic refrigerators and freezers in use today.

Yuma, AZ is the sunniest place on the planet, getting over 4,000 hours of sunshine per year!

The average American woman owns 30 outfits – on for every day of the month.

TVs in the average U.S home are turned on for more than a third of the day – 8 hours, 14 minutes!

The average U.S. house has 300,000 things in it.

We apparently only use 20% of the things we own.

"statistik bisa membantu kita merencanakan liburan ke bali bulan desember "

well hello bali

Can you do a video on biostatics please.

my questions on this lesson

5:09, because stats can only answer some questions, do you think stats could be wrong on certain questions because it may be a study of the majority. So some people may eat fast food and become stressed, but others could eat fast food to de-stress, and could stats figure out which one I am more likely to be eating fast food for?

Any tea lover will know. It's like coffee drinkers sometimes put their milk in first. Sometimes making up a drink I'll put water the flavoring in….

Boring

Thanks!

I have statistics this year and I’m super confused 😀

Only 148% of people understand statistics.

WOW…..I have never liked or understood math at all but having to take math for my degree in ECE & finding out that statistics would count….I thought why not look into statistics & see if I can understand it…..& OMG the way you explain things makes me think I can actually GET THIS!!!!….. Totally switching classes now!!!!!