Unit 2 AP Stats Review

0.0(0)
studied byStudied by 18 people
learnLearn
examPractice Test
spaced repetitionSpaced Repetition
heart puzzleMatch
flashcardsFlashcards
Card Sorting

1/23

Study Analytics
Name
Mastery
Learn
Test
Matching
Spaced

No study sessions yet.

24 Terms

1
New cards

bivariate

two variables

2
New cards

what are we interested in when exploring bivariate data

whether not/how changes in one variable can allow us to predict changes in the other variable

3
New cards

scatterplot

2-dimensional graph of ordered pairs

4
New cards

what do we say about positively associated variables

higher than average values of one variable TEND TO BE PAIRED WITH higher than average values of the other variable

5
New cards

correlation coefficient (r) is a measure of what?

the strength of the LINEAR relationship between 2 variables, as well as the direction of this relationship (+ or -)

6
New cards

if r is equal to the absolute value of 1…

all points lie on a line

7
New cards

if abs(r) is greater than .8…

the LINEAR correlation is generally regarded to be strong

8
New cards

if abs(r) is between .5 & .8…

the LINEAR correlation is generally regarded to be moderateif

9
New cards

if abs(r) is less than .5…

the LINEAR correlation is generally regarded to be weak

10
New cards

if r is = 0, there is…

no LINEAR correlation (may be nonlinear correlation)

11
New cards

if you change the order of the explanatory/dependent variables, what effect will this change have on r?

none!

12
New cards

if you change the units of measurement of one of your variables (e.g. ft to yrds), what effect will this change have on r?

none!

13
New cards

is r resistant to extreme values? why/why not?

no; r is based on the MEAN & is effected by extreme values

14
New cards

least squares regression line does what?

minimizes the sum of squared errors/distances of points from our line

15
New cards

residual

difference between the observed values of the response variable (y) and the predicted values (ŷ) from the model

16
New cards

a negative residual means that ŷ was too…

large

17
New cards

a positive residual means that ŷ was too…

small

18
New cards

a pattern of residuals that doesn’t appear to be randomly distributed about 0 indicates…

a regression line that isn’t a good model of our data

19
New cards

interpolation

trying to predict a value of y from a value of x which is WITHIN the range of x-values we have (your traditional prediction, think internal)

20
New cards

extrapolation

trying to predict a value of y from a value of x which ISN’T within the range of x-values we have (unadvised, rarely have confidence, think external)

21
New cards

coefficient of determination

r^2; the proportion of the total variability in y which is explained by the regression of y on x

22
New cards

outlier when dealing with bivariate data…

lies outside the general pattern of data (for regression, datapoint has a LARGE RESIDUAL)

23
New cards

influential observation

an observation that has a strong influence on the regression model; most influential points tend to be extreme in the x direction (high LEVERAGE points)

24
New cards