AP STATS

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.

Question 3

What are the 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 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 to inferential Stats.

Answer 6

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

Question 7

What are data?

Answer 7

Any collected information. Generally each little itsy bitsy measurement… Like, if it is a survey about porridge… the data might be “yes, yes,no,yes,yes,” if it is the number of saltines someone can eat in under 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 its big like “all teenagers in the US.” Other times it’s small like “ All the AP Stats students in my school.”

Question 9

What is a sample?

Answer 9

A subset of a population, often take to make inferences about a population. We calculate statistic from samples.

Question 10

Compare population to sample.

Answer 10

Populations are generally large and samples are small subsets of a 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 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. Statistics is the result of data analysis. Its interpretation and presentation.

Question 12

Compare Data to Parameters.

Answer 12

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 every member of the population, then that mean is called a parameter.

Question 13

What is a parameter?

Answer 13

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

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 dunking 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 each individual car, so that would be like “3.8 min, 2.2 min, 0.8 min, 3 min.”You take that data and find the average.The 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 data.

Answer 16

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

Question 17

Compare Data-Statistic-Parameter using Quantitative data.

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 sec”

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 a small population( 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 parameters come from populations and statistics come from samples.

Question 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 ___?

Answer 21

A datum or a data value

Question 22

If I take a random sample of 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( It 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. 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

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

Answer 25

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

Question 26

If you are tasting soup.. Then the flavor of each individual thing in the spoon is the 1. _____, the entire spoon is a 2. _____.. The flavor of all of that stuff together is like the 3.___ and you use that to 4. ____ about the flavor of the entire pot of soup, which would be the 5.____.

Answer 26

1. Data 2. Sample 3.Statistic 4.Make an Inference 5. Parameter

Question 27

What are random variables?

Answer 27

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 28

What is the difference between quantitative and categorical variables?

Answer 28

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

Question 29

What is the difference between quantitative and categorical data?

Answer 29

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 simply “yes, yes, yes, no, yes, no.” If it was weight, then the data would be quantitative like “125, 155, 223, 178, 222, ect…” The data from quantitative variables are numbers.

Question 30

What is the difference between discrete and continuous variables?

Answer 30

Discrete can be accounted, 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 31

What is a quantitative variable?

Answer 31

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

Question 32

What is a categorical variable?

Answer 32

Qualitative variables are like categories: Blondes, Listens to Hip Hop, Female, yes, no,… etc

Question 33

What do we sometimes call a categorical variable?

Answer 33

Qualitative

Question 34

What is a quantitative data?

Answer 34

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

Question 35

What is categorical data?

Answer 35

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

Question 36

What is a random sample?

Answer 36

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 37

What is frequency?

Answer 37

How often something comes up.

Question 38

data or datum?

Answer 38

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

Question 39

What is a frequency distribution?

Answer 39

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

Question 40

What is meant by relative frequency?

Answer 40

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

Question 41

How do you find relative frequency?

Answer 41

just divide frequency by the total

Question 42

What is meant by cumulative frequency?

Answer 42

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 43

Make a guess as to what relative cumulative frequency is

Answer 43

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 the by the total giving cumulative percentages…, 0.40, 0.60, 0.64 and 1. Relative cumulative frequencies always end at 100 percent.

Question 44

What is the difference between a bar chart and a histogram

Answer 44

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

Question 45

What is the mean?

Answer 45

The old average we used to calculate. It is the balancing point of the histogram.

Question 46

What is the difference between a population mean and a sample mean?

Answer 46

Population mean is the mean of a population, it is a parameter, sample mean is a mean of a sample, so it is a statistic. We use sample statistics to make inferences about population parameters.

Question 47

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

Answer 47

Mu for population mean and xbar for sample mean.

Question 48

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

Answer 48

Mean is balancing point of histogram, median splits the are of the histogram in half.

Question 49

What is the median?

Answer 49

The middles number, it splits are in half (always in the positions (n+1)/2)

Question 50

What is mode?

Answer 50

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

Question 51

When do we often use mode?

Answer 51

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

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 the skewness and outliers.

Question 53

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

Answer 53

It depends if we are talking about 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.