Summer Vocab

Question 1

What is statistics?

Answer 1

Study of variability

Question 2

Variability?

Answer 2

Differences, or how things are different

Question 3

2 branches of statistics?

Answer 3

inferential and descriptive

Question 4

Descriptive

Answer 4

Describing the data… i.e. mean, median, mode, range

Question 5

Inferential

Answer 5

Using the data to talk about the bigger picture

Question 6

Differences between descriptive and inferential

Answer 6

Descriptive explains the data while inferential uses the data to say something about the entire population

Question 7

What is data?

Answer 7

Any collected information

Question 8

What is a population?

Answer 8

The group of people that you are interested in

Question 9

What is a sample?

Answer 9

The portion of the population that data is being taken from. Statistics come from a sample

Question 10

Compare population to sample

Answer 10

A population is a generally a large group while a sample is a subset of that population. We use samples to make inferences about the population, and we use the population to make 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

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
statistics.`

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/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.