Summer Vocab

Question 1

What is Statistics?

Answer 1

The study of Variability

Question 2

What is Variability?

Answer 2

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

Question 3

What are 2 branches of AP STATS?

Answer 3

Inferential and Descriptive

Question 4

What are Descriptive STATS?

Answer 4

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

Question 5

What are Inferential STATS?

Answer 5

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)

Question 6

Compare Descriptive and Inferential STATS

Answer 6

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

Question 7

What is Data?

Answer 7

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”

Question 8

What is a Population?

Answer 8

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

Question 9

What is a Sample?

Answer 9

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

Question 10

Compare Population to Sample

Answer 10

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.

Question 11

Compare Data to Statistics

Answer 11

Data is each little bit of information collected from the subject…. 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 the mean a “statistic” if we have data from each member of population, then that mean is called a “parameter”

Question 12

Compare Data to Parameter

Answer 12

Data is each little bit of information collected from the subject…. 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 the mean a “statistic” if we have data from each member of population, then that mean is called a “parameter”

Question 13

What is a Parameter?

Answer 13

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

Question 14

What is a statistic?

Answer 14

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

Question 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?

Answer 15

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.

Question 16

Compare DATA-STATISTIC-PARAMETER using categorical example

Answer 16

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.?

Question 17

Compare DATA-STATISTIC-PARAMETER using quantitative example

Answer 17

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?

Question 18

What is a census?

Answer 18

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

Question 19

Does a census make sense?

Answer 19

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

Question 20

What is the difference between a parameter and a statistic?

Answer 20

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

Question 21

f 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 ____?

Answer 21

a datum, or a data value.

Question 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 _______?

Answer 22

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

Question 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 ______?

Answer 23

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

Question 24

What is the difference between a sample and a census?

Answer 24

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.

Question 25

What are DESCRIPTIVE STATS?

Answer 25

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

Question 26

What are INFERENTIAL STATS?

Answer 26

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)

Question 27

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

Answer 27

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).

Question 28

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__________.

Answer 28

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.

Question 29

What are random variables?

Answer 29

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.

Question 30

What is the difference between quantitative and categorical variables?

Answer 30

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

Question 31

What is the difference between quantitative and categorical data?

Answer 31

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.

Question 32

What is the difference between discrete and continuous variables?

Answer 32

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.

Question 33

What is a quantitative variable?

Answer 33

Quantitative variables are numeric like: Height, age, number of cars sold, SAT score

Question 34

What is a categorical variable?

Answer 34

Qualitative variables are like categories: Blonde, Listens to Hip Hop, Female, yes, no? etc.

Question 35

What do we sometimes call a categorical variable?

Answer 35

qualitative

Question 36

What is quantitative data?

Answer 36

The actual numbers gathered from each subject. 211 pounds. 67 beats per minute.

Question 37

What is categorical data?

Answer 37

The actual individual category from a subject, like “blue” or “female” or “sophomore”

Question 38

What is a random sample?

Answer 38

When you choose a sample by rolling dice, choosing names from a hat, or other REAL RANDOMLY generated sample. Humans can’t really do this well without the help of a calculator, cards, dice, or slips of paper.

Question 39

What is frequency?

Answer 39

How often something comes up

Question 40

data or datum?

Answer 40

datum is singular.. Like “hey dude, come see this datum I got from this rat!” data is the plural.. “hey look at all that data Edgar got from those chipmunks over there!!”

Question 41

What is a frequency distribution?

Answer 41

A table, or a chart, that shows how often certain values or categories occur in a data set.

Question 42

What is meant by relative frequency?

Answer 42

The PERCENT of time something comes up (frequency/total)

Question 43

What is meant by cumulative frequency?

Answer 43

ADD up the frequencies as you go. Suppose you are selling 25 pieces of candy. You sell 10 the first hour, 5 the second, 3 the third and 7 in the last hour, the cumulative frequency would be 10, 15, 18, 25

Question 44

Make a guess as to what relative cumulative frequency is?

Answer 44

It is the ADDED up PERCENTAGES.. An example is selling candy, 25 pieces sold overall…, with 10 the first hour, 5 the second, 3 the third, and 7 the fourth hour, we’d take the cumulative frequencies, 10, 15, 18 and 25 and divide by the total giving cumulative percentages… .40, .60, .64, and 1.00. Relative cumulative frequencies always end at 100 percent.

Question 45

What is the difference between a bar chart and a histogram

Answer 45

bar charts are for categorical data (bars don’t touch) and histograms are for quantitative data (bars touch)

Question 46

What symbols do we use for population mean and sample mean?

Answer 46

Mu for population mean, xbar for sample mean.

Question 47

How can you think about the mean and median to remember the difference when looking at a histogram?

Answer 47

mean is balancing point of histogram, median splits the area of the histogram in half.

Question 48

What is the median?

Answer 48

the middlest number, it splits area in half (always in the POSITION (n+1)/2 )

Question 49

What is the mode?

Answer 49

the most common, or the peaks of a histogram. We often use mode with categorical data

Question 50

When do we often use mode?

Answer 50

With categorical variables. For instance, to describe the average teenagers preference, we often speak of what ?most? students chose, which is the mode. It is also tells the number of bumps in a histogram for quantitative data (unimodal, bimodal, etc?).

Question 51

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?

Answer 51

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.

Question 52

Why don’t we always use the mean, we’ve been calculating it all of our life ?

Answer 52

It is not RESILIENT, it is impacted by skewness and outliers

Question 53

When we say “the average teenager” are we talking about mean, median or mode?

Answer 53

It depends, if we are talking height, it might be the mean, if we are talking about parental income, we’d probably use the median, if we were talking about music preference, we’d probably use the mode to talk about the average teenager.