Lecture 10

Question 1

what does correlation describe

Answer 1

an association between variables. when one variable changes, so does the other

Question 2

what does causation mean

Answer 2

that changes in one variable brings about changes in the other; there is a cause-and-effect relationship between variables

Question 3

what is the correlation coefficient?

Answer 3

a measure of the average distance of all of the points from an imaginary straight line drawn through the scatter of points.

Question 4

what does Pearson’s correlation coefficient measure?

Answer 4

the strength of the linear association between two variables

Question 5

Pearson’s correlation coefficient value from -1 indicates?

Answer 5

perfect negative correlation (all the points exactly on a line)

Question 6

Pearson’s correlation coefficient value from 0 indicates?

Answer 6

no association

Question 7

Pearson’s correlation coefficient value from +1 indicates?

Answer 7

indicating perfect positive correlation (all points exactly on a line)

Question 8

when can we run spearman’s test?

Answer 8

when the variables are not normally distributed;

sample size<20

Question 9

is spearmans test a parametric measure?

Answer 9

no, its non-parametric

Question 10

what is a similarity between pearsons and spearmans test?

Answer 10

the coefficient varies form -1 to +1

Question 11

define covariance

Answer 11

Covariance measures how two variables move with respect to each other and is an extension of the concept of variance (which tells about how a single variable varies). It can take any value from -∞ to +∞

Question 12

what a positive number signifies in covariance?

Answer 12

it signifies positive covariance, and denotes that a direct relationship exists

Question 13

what a negative number signifies in covariance?

Answer 13

negative covariance, which denotes an inverse relationship between two variables

Question 14

is covariance good for interpreting the magnitude of the relationship?

Answer 14

no, its only good for defining relationship type

Question 15

what is one property of covariance matrix?

Answer 15

it is always symmetric with the variances on its diagonal and the covariances off-diagonal

Question 16

define linear regression

Answer 16

the prediction of value of one characteristic from knowledge of another. must be two variables and their relationship is displayed in a straight line

Question 17

how many independent variables are included in multiple regression?

Answer 17

more than one independent variable is included in the prediction equation

Question 18

define dependent variable

Answer 18

s the variable whose values you want to predict

Question 19

define independent variable

Answer 19

is the variable which you use to predict the dependent variable

Question 20

define coefficient of determination

Answer 20

a statistical measurement that examines how differences in one variable can be explained by the difference in a second variable, when predicting the outcome of a given event

Question 21

define residual

Answer 21

The difference between the predicted value (based on the regression equation) and the actual, observed value

Question 22

define outlier

Answer 22

In linear regression, an outlier is an observation with large residual. In other words, it is an observation whose dependent-variable value is unusual given its value on the predictor variables. An outlier may indicate a sample peculiarity or may indicate a data entry error or other problem

Question 23

define leverage

Answer 23

Leverage is a measure of how far an independent variable deviates from its mean. High leverage points can have a great amount of effect on the estimate of regression coefficients

Question 24

define influence

Answer 24

An observation is said to be influential if removing the observation substantially changes the estimate of the regression coefficients. Influence can be thought of as the product of leverage and outlierness

Question 25

define cooks distance

Answer 25

A measure that combines the information of leverage and residual of the observation.