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1

What is Statistics?

The study of variability

2

What is variability?

Differences... how things differ. There is variability everywhere.. We all look different, act different, have different preferences... Statisticians look at these differences.

3

What are 2 branches of AP STATS?

Inferential and Descriptive

4

What are DESCRIPTIVE STATS?

Tell me what you got! Describe to me the data that you collected, use pictures or summaries like mean, median, range, etc...

5

What are INFERENTIAL STATS?

Look at your data, and use that to say stuff about the BIG PICTURE... like tasting soup... a little sample can tell you a lot about the big pot of soup (the population)

6

Compare Descriptive and Inferential STATS

Descriptive explains you about the data that you have, inference uses that data you have to try to say something about an entire population....

7

What is data?

Any collected information. Generally each little measurement... Like, if it is a survey about liking porridge... the data might be “yes, yes, no, yes, yes” if it is the number of saltines someone can eat in 30 seconds, the data might be “3, 1, 2, 1, 4,3 , 3, 4”

8

What is a population?

the group you're interested in. Sometimes it’s big, like "all teenagers in the US" other times it is small, like "all AP Stats students in my school"

9

What is a sample?

A subset of a population, often taken to make inferences about the population. We calculate statistics from samples.

10

Compare population to sample

populations are generally large, and samples are small subsets of these population. We take samples to make inferences about populations. We use statistics to estimate parameters.

11

Compare data to statistics

Data is each little bit of information collected from the subjects.... They are the INDIVIDUAL little things we collect... we summarize them by, for example, finding the mean of a group of data. If it is a sample, then we call that mean a "statistic" if we have data from each member of population, then that mean is called a "parameter"

12

Compare data to parameters

Data is each little bit of information collected from the subjects.... They are the INDIVIDUAL little things we collect... we summarize them by, for example, finding the mean of a group of data. If it is a sample, then we call that mean a "statistic" if we have data from each member of population, then that mean is called a "parameter"

13

What is a parameter?

A numerical summary of a population. Like a mean, median, range... of a population

14

What is a statistic?

A numerical summary of a sample. Like a mean, median, range... of a sample.

15

We are curious about the average wait time at a Dunkin Donuts drive through in your neighborhood. You randomly sample cars one afternoon and find the average wait time is 3.2 minutes. What is the population parameter? What is the statistic? What is the parameter of interest? What is the data?

The parameter is the true average wait time at that Dunkin Donuts. This is a number you don't have and will never know. The statistic is "3.2 minutes." It is the average of the data you collected. The parameter of interest is the same thing as the population parameter. In this case, it is the true average wait time of all cars. The data is the wait time of each individual car, so that would be like "3.8 min, 2.2 min, .8 min, 3 min". You take that data and find the average, that average is called a "statistic," and you use that to make an inference about the true parameter.

16

Compare DATA-STATISTIC- PARAMETER using categorical example

Data are individual measures... like meal preference: “taco, taco, pasta, taco, burger, burger, taco”... Statistics and Parameters are summaries. A statistic would be “42% of sample preferred tacos” and a parameter would be “42% of population preferred tacos.”

17

Compare DATA-STATISTIC- PARAMETER using quantitative example

Data are individual measures, like how long a person can hold their breath: “45 sec, 64 sec, 32 sec, 68 sec.” That is the raw data. Statistics and parameters are summaries like “the average breath holding time in the sample was 52.4 seconds” and a parameter would be “the average breath holding time in the population was 52.4 seconds”

18

What is a census?

Like a sample of the entire population, you get information from every member of the population

19

Does a census make sense?

A census is ok for small populations (like Mr. Nystrom's students) but impossible if you want to survey "all US teens"

20

What is the difference between a parameter and a statistic?

BOTH ARE A SINGLE NUMBER SUMMARIZING A LARGER GROUP OF NUMBERS.... But pppp parameters come from pppp populations... sss statistics come from ssss statistics.

21

If I take a random sample of 20 hamburgers from FIVE GUYS and count the number of pickles on a bunch of them... and one of them had 9 pickles, then the number 9 from that burger would be called ____?

a datum, or a data value.

22

If I take a random sample 20 hamburgers from FIVE GUYS and count the number of pickles on a bunch of them... and the average number of pickles was 9.5, then 9.5 is considered a _______?

statistic. (t is a summary of a sample.)

23

If I take a random sample of 20 hamburgers from FIVE GUYS and count the number of pickles on a bunch of them... and I do this because I want to know the true average number of pickles on a burger at FIVE GUYS, the true average number of pickles is considered a ______?

parameter, a one number summary of the population. The truth. AKA the parameter of interest.

24

What is the difference between a sample and a census?

With a sample, you get information from a small part of the population. In a census, you get info from the entire population. You can get a parameter from a census, but only a statistic from a sample.

25

se the following words in one sentence: population, parameter, census, sample, data, statistics, inference, population of interest.

I was curious about a population parameter, but a census was too costly so I decided to choose a sample, collect some data, calculate a statistic and use that statistic to make an inference about the population parameter (aka the parameter of interest).

26

If you are tasting soup.. Then the flavor of each individual thing in the spoon is the ________, the entire spoon is a ______.. The flavor of all of that stuff together is like the _____ and you use that to __________ about the flavor of the entire pot of soup, which would be the__________.

If you are tasting soup. Then the flavor of each individual thing in the spoon is DATA, the entire spoon is a SAMPLE. The flavor of all of that stuff together is like the STATISTIC, and you use that to MAKE AN INFERENCE about the flavor of the entire pot of soup, which would be the PARAMETER. Notice you are interested in the parameter to begin with... that is why you took a sample.

27

What are random variables?

If you randomly choose people from a list, then their hair color, height, weight and any other data collected from them can be considered random variables.

28

What is the difference between quantitative and categorical variables?

Quantitative variables are numerical measures, like height and IQ. Categorical are categories, like eye color and music preference

29

What is the difference between quantitative and categorical data?

The data is the actual gathered measurements. So, if it is eye color, then the data would look like this "blue, brown, brown, brown, blue, green, blue, brown... etc." The data from categorical variables are usually words, often it is simpy "YES, YES, YES, NO, YES, NO" If it was weight, then the data would be quantitative like "125, 155, 223, 178, 222, etc.." The data from quantitative variables are numbers.

30

What is the difference between discrete and continuous variables?

Discrete can be counted, like "number of cars sold" they are generally integers (you wouldn't sell 9.3 cars), while continuous would be something like weight of a mouse... 4.344 oz.