AP Stats guy

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 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 big, like “all teenagers in the US”
other times it 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 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”

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 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 a mean, median, range… of a
population

Question 14

What is a statistic?

Answer 14

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

Question 15

What is the difference between a parameter and a statistic?

Answer 15

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

Question 16

What is the difference between quantitative and categorical

variables?

Answer 16

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

Question 17

What is the difference between quantitative and categorical data?

Answer 17

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 18

What is the difference between discrete and continuous variables?

Answer 18

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 19

What is a quantitative variable?

Answer 19

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

Question 20

What is a categorical variable?

Answer 20

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

Question 21

What is meant by relative

frequency?

Answer 21

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

Question 22

How do you find relative frequency?

Answer 22

just divide frequency by TOTAL….

Question 23

What is meant by cumulative frequency?

Answer 23

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 24

What is the difference between a bar chart and a histogram

Answer 24

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

Question 25

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

Answer 25

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 26

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

Answer 26

Mu for population mean (parameter), x-bar ̅ for sample mean (statistic)

Question 27

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

Answer 27

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

Question 28

What is the median?

Answer 28

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

Question 29

What is the mode?

Answer 29

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

Question 30

When do we often use mode?

Answer 30

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 31

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

Answer 31

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

Question 32

How are mean, median and mode positioned in a skewed left histogram?

Answer 32

goes in that order from left to right. Mean-median-mode

Question 33

How are mean, median and mode positioned in a skewed right

histogram?

Answer 33

goes in the opposite order.. Mode-median-mean