Regression Analysis

Question 1

regression analysis

Answer 1

the study of the dependence of one variable

Question 2

correlation analysis

Answer 2

measure the strength or degree of linear association between two variables
ex. correlation between smoking and lung cancer

Question 3

explanatory variable

Answer 3

same as independent variable

Question 4

simple regression

Answer 4

studies the dependence of a variable only on a single explanatory variable

Question 5

multiple regression

Answer 5

one dependent variable but multiple independent variables

Question 6

time series data

Answer 6

a set of observations on the values that a variable takes at different times

Question 7

cross-sectional data

Answer 7

data of one or more variables collected at the same point in time

Question 8

multiple regression formula

Answer 8

Y = B(0) + B(1)X(1)+… B(n)X(n) + error

big B = whole population
small b = sample (estimated)

Question 9

B(0)

Answer 9

intercept term

can be interpreted as the average effect on Y of all the variables excluded from the model

Question 10

ordinary least squares

Answer 10

method of fitting a straight line to a sample of data

Question 11

R squared

Answer 11

measures how well the estimated regression fits the data (how close to the line it is)

from 0 -1
the higher the value the higher the quality of the model

Question 12

adjusted r squared

Answer 12

same as r squared but for more variables to avoid overestimating the impact of adding an independent variable

Question 13

F-test

Answer 13

overall significance

shows if there is a linear relationship between all of the x variables considered together and y

Question 14

f-test conclusions

Answer 14

p-value < 5% then reject the null hypothesis and x is significant in explaining y

p-value > 5% cannot reject the null hypothesis and x is not significant

Question 15

null hypothesis

Answer 15

no statistical significance exists

attempts to show that a single variable is no different than 0