Regression

Question 1

Pearsons Correlation (r)

Answer 1

strength and direction of linear relationship of 2 quant variables

Question 2

Spearman’s correlation (p)

Answer 2

strength and direction of monotone relationship
-more robust to outliers
-nonlinear relationships

Question 3

regression

Answer 3

linear relationship between 2 quant variables
use the explanatory variable to predict the response
variables
Y= b0(intercept) + b1(slope)X(explanatory variable)

Question 4

residual

Answer 4

the diffrence between an observed value and a prediction

+ under predicted
- over predicted

Question 5

coefficient of determination R2

Answer 5

how close observations match the predictions
0-1

Question 6

linear regression

Answer 6

putting a line in a scatterplot to describe the relationship between the variables

Question 7

Interpret- Linear regression Intercept

Answer 7

-The intercept represents the value of Y when the independent variable X is 0

Question 7

Interpret-Linear regression SLOPE

Answer 7

The slope indicates how much the dependent variable (Y) is expected to change for each one-unit increase in the independent variable (X).
- positive, there is a positive relationship
-negative, there is a negative relationship