Studied by 18 people

0.0(0)

Get a hint

Hint

1

bivariate

two variables

New cards

2

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

New cards

3

scatterplot

2-dimensional graph of ordered pairs

New cards

4

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

New cards

5

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 -)

New cards

6

if r is equal to the absolute value of 1â€¦

all points lie on a line

New cards

7

if abs(r) is greater than .8â€¦

the LINEAR correlation is generally regarded to be strong

New cards

8

if abs(r) is between .5 & .8â€¦

the LINEAR correlation is generally regarded to be moderateif

New cards

9

if abs(r) is less than .5â€¦

the LINEAR correlation is generally regarded to be weak

New cards

10

if r is = 0, there isâ€¦

no LINEAR correlation (may be nonlinear correlation)

New cards

11

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

none!

New cards

12

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!

New cards

13

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

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

New cards

14

least squares regression line does what?

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

New cards

15

residual

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

New cards

16

a negative residual means that Ĺ· was tooâ€¦

large

New cards

17

a positive residual means that Ĺ· was tooâ€¦

small

New cards

18

a pattern of residuals that doesnâ€™t appear to be randomly distributed about 0 indicatesâ€¦

a regression line that isnâ€™t a good model of our data

New cards

19

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)

New cards

20

extrapolation

trying to predict a value of y from a value of x which ISNâ€™T within the range of x-values we have (unadvised, rarely have confidence, think external)

New cards

21

coefficient of determination

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

New cards

22

outlier when dealing with bivariate dataâ€¦

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

New cards

23

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)

New cards

24

New cards