AP Stats

Question 1

categorical variable

Answer 1

labels that place each individual into a particular group
ex: race, sex, age group

Question 1

quantitative

Answer 1

takes number values that are quantities, counts, or measurements
ex: height, weight, cost

Question 2

quantitative discrete

Answer 2

a fixed set of possible values
ex: how many green marbles you draw out of a bag

Question 3

quantitative continuous

Answer 3

any value in an interval on the number line
ex: time

Question 4

relative frequency table

Answer 4

shows the proportion or percent of individuals having each value.

Question 5

two-way table

Answer 5

a table of counts that summarizes data on the relationship between two categorical variables for some group of individuals.

Question 6

categorical graphs

Answer 6

• Pie Charts
• Pictographs
• Dot-plots
• Bar Graphs
• Side-by-side Bar Graphs
• Segmented Bar Graphs
• Mosaic Plots

Question 7

Association

Answer 7

if knowing the value of one variable
helps us predict the value of the other

Question 8

Simpson’s Paradox

Answer 8

a contradiction between what we see when looking at individual
categories and the subtotals for our distributions when dealing with categorical
variables

Question 9

Quantitative Graphs

Answer 9

• Dot-plots
• Stem-plots
• Histogram
• Boxplots
• Ogives

Question 10

how we describe distributions

Answer 10

CUSS + BS
-C: center
-U: unusual outliers
-S: spread
-S: shape
-BS: be specific

Question 11

mean

Answer 11

average of all individual data values

Question 12

Statistic

Answer 12

a number that describes some characteristic of a sample
-ex: asking 20 random people their height and averaging results

Question 13

Parameter

Answer 13

a number that describes some characteristic of a population
-ex: asking everyone in the population
their height and averaging results

Question 14

Range

Answer 14

difference between the maximum value
and the minimum value

Question 15

Standard Deviation

Answer 15

the typical or average distance of the values in a distribution from the _mean

Question 16

Interquartile Range (IQR)

Answer 16

IQR = Q3 – Q1

Question 17

lower Outlier Test

Answer 17

Lower Outliers < Q1 – 1.5(IQR)

Question 18

higher outlier test

Answer 18

Higher Outliers > Q3 + 1.5(IQR)

Question 19

response variable

Answer 19

measures an outcome of a study

Question 20

explanatory variable

Answer 20

may help predictor explain changes in a
response variable

Question 21

population

Answer 21

the entire group we want to know about

Question 22

census

Answer 22

collects data from every individual in a population

Question 23

sample

Answer 23

a subset of individuals in the population

Question 24

population parameter

Answer 24

ex: google says that 79% of people everywhere have a dog *it's from everyone

Question 25

sample statistic

Answer 25

student asks 100 people if they have a dog and 70% say yes *it's from a small sample

Question 26

convenience sampling

Answer 26

selects individuals who are easy to reach

Question 27

voluntary response sampling

Answer 27

allows people to respond if they want to

Question 28

SUDS

Answer 28

*Used for describing data -S: strength (strong, moderate, weak) -U: unusual values (outliers) -D: direction (positive, negative) -S: Shape (bell, Bimodal, skewed, uniform)

Question 29

correlation(r)

Answer 29

measures the direction and strength: -strong: close to 1 or -1 -does not imply causation -does not measure form -only for linear relationships

Question 30

Regression Line(LSRL)

Answer 30

line that models how a response variable y changes as an an explanatory variable x changes ŷ=a+bx

Question 31

ŷ=a+bx

Answer 31

ŷ: predicted y a: y-intercept(a=ȳ -bx̄) b: slope(b= r sy/sx) x: x variable

Question 32

extrapolation

Answer 32

uses the regression to predict a value outside of the interval

Question 33

residual

Answer 33

actual y - predicted y OR (y-ŷ)

Question 34

least squared regression line(LSRL)

Answer 34

the sum of the squared residuals as small as possible

Question 35

coefficient of determination(r²)

Answer 35

n% of variability in y can be explained by the linear model

Question 36

stratified random sampling

Answer 36

selects a sample by choosing an SRS from each group and combining the SRSs into one big sample

Question 37

cluster sampling

Answer 37

selects a sample by randomly choosing clusters and including each member of selected clusters in the sample

Question 38

systemic random sampling

Answer 38

selects a sample from an ordered arrangement of the population by randomly selecting one of the first k individuals and choosing every kth after that

Question 39

under-coverage

Answer 39

when some members of the population are less likely to be chosen or can't be chosen for a sample

Question 40

non-response

Answer 40

when an individual chosen for tyhe sample cannot be contacted or refuses to answer

Question 41

response bias

Answer 41

when there is a systematic pattern of inaccurate answers

Question 42

observational

Answer 42

observes results without trying to influence them

Question 43

experiment

Answer 43

deliberately and randomly imposes treatments to measure responses

Question 44

confounding

Answer 44

when two variables are associated in such a way that their effects on a response variable cannot be distinguished from each other

Question 45

principles of experimental design

Answer 45

1.) how many in each 2.) randomization 3.) repeats? 4.) rest/stop 5.) assign to treatment groups

Question 45

match pair design

Answer 45

a common experimental design for comparing two treatments that use blocks of 2

Question 45

block

Answer 45

a group of experimental units that are known before the experiment to be similar in some way in terms of response to treatment

Question 46

random selection

Answer 46

allows inference about the population from which the individuals were chosen

Question 47

random assignment

Answer 47

allows for inference about cause and effect

Question 48

law of large numbers

Answer 48

if we observe more and more trials of any random process, the proportion of times that a specific outcome occurs approaches its probability

Question 49

mutually exclusive

Answer 49

when you have one, you CANT have the other

Question 50

categorical conditions

Answer 50

☑ randomization ☑ independence OR 10% rule ☑ np rules

Question 51

quantitative conditions

Answer 51

☑ randomization ☑ independence OR 10 % rule ☑ central limits theorem: n>30