Summer Vocab

Question 1

Statistics

Answer 1

Study of variability

Question 2

population

Answer 2

group of interest, can be big or small

Question 3

Variability

Answer 3

All things have differences, and statisticians look a these differences

Question 4

2 branchs of AP stats

Answer 4

inferential and descriptive

Question 5

descriptive stats

Answer 5

describe collected data using pictures or summaries like mean, median, range, etc…

Question 6

inferential stats

Answer 6

look at data of sample and use it to tell about the population

Question 7

compare descriptive and inferential stats

Answer 7

descriptive explains about data; inferential uses data of sample to tell about an entire population

Question 8

data

Answer 8

any collected info., generally each little measurement

Question 9

sample

Answer 9

A subset of population, taken to make inferences about the population, calculate statistics from samples

Question 10

compare population to sample

Answer 10

populations generally are large, samples are small subsets of population; take samples to make inferences about populations, use statistics to estimate parameters

Question 11

compare data to statistics

Answer 11

data is the individual bits of info collected, summarize data by, ex. finding mean of a group of data,
mean of sample is statistic, if data is from each member of population, mean is parameter

Question 12

compare data to parameters

Answer 12

data is the individual bits of collected info, summarize data by, ex. finding mean of a group of data,
mean of sample is statistic, summary of sample; if data is from each member of population, mean is parameter, summary of population

Question 13

parameter

Answer 13

numerical summary of a population like mean, median, mode

Question 14

statistic

Answer 14

numerical summary of a sample like mean, median, mode

Question 15

Curious about average wait a Dunkin Donuts drive through: randomly sample cars and find the average wait time is 3.2 minutes. What is the population parameter, statistic, parameter of interest, data?

Answer 15

parameter is the true average wait time at that Dunkin Donuts, a number you don’t have and will never know. Statistic is 3.2 minutes, average of data collected. Parameter of interest= population parameter. Data is the wait time of each individual car, like “3.8 min, 2.2 min, 0.8 min.” Average of that data is statistic, and use that to make inference about the true parameter

Question 16

Compare DATA-STATISTICPARAMETER 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-STATISTICPARAMETER 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….

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

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

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 data, 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 ________, 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 26

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 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 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 30

What is the difference between | discrete and continuous variables?

Answer 30

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 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: Blonde, 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 quantitative data?

Answer 34

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

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 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 39

What is a frequency distribution?

Answer 39

A table, or a 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 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 by the total giving cumulative percentages... .40, .60, .64, and 1.00. 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 (parameter), x-bar ̅ for sample mean (statistic)

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 area of the histogram in half.

Question 49

What is the median?

Answer 49

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

Question 50

What is the 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 is also tells the number of bumps in a histogram for quantitative data (unimodal, bimodal, etc…).

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.

Question 54

what is a clear example of where the mean would change but median wouldn't? (this would show its resilience)

Answer 54

Imagine if we asked eight people how much money they had in their wallet. We found they had {1, 2, 2, 5, 5, 8, 8, 9}. The mean of this set is 5, and the median is also 5. You might say "the average person in this group had 5 bucks." But imagine if one of them just got back from the casino, and instead it was (1, 2, 2, 5, 5, 8, 8, 9000}, in this case, the median would still be 5, but the mean goes up to over 1000. Which number better describes the amount of money the average person in the group carries, 5 bucks or 1000 bucks? I think 5 is a better description of the average person in this group and the 9000 is simply an outlier.

Question 55

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

Answer 55

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

Question 56

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

Answer 56

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

Question 57

Who chases the tail?

Answer 57

The mean chases the tail, the mean chases the tail, high-ho the derry-oh the mean chases the tail… and outliers…….

Question 58

Is there a way to study these efficiently instead of just rereading them?

Answer 58

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