Topic: Bivariate Linear Regression Analysis

Q1: Suppose a study is conducted to investigate the relationship between the scores students receive on their Midterm and final tests. Based on the following sample, find the correlation coefficient :

Mid Final

180 280

195 280

210 300

225 316

240 320

255 350

255 370

264 320

265 400

290 350

a. 0.566

b. 0.645

c. 0.738

d. 0.802

e. 0.905

Q2. The error term is the difference between an individual value of the dependent variable and the corresponding mean value of the dependent variable.

True or False

Q3. The following assumption about the error term is incorrect

a. Errors are normally distributed

b. The mean of error terms is zero

c. Error terms have a constant variance

d. Error terms depend on the explanatory variable

e. Error terms are uncorrelated across observations

Q4. The Least Squares Regression minimizes the sum of

a. deviations between actual and predicted Y values

b. squared deviations between actual and predicted X values

c. absolute deviations between actual and predicted Y values

d. absolute deviations between actual and predicted X values

e. squared deviations between actual and predicted Y values

Q5. The coefficient of Determination only indicates the strength of the relationship between the independent and dependent variables but does not reveal the direction of the relationship (positive or negative).

True or False

Q6. When using simple regression analysis, if there is a strong correlation between the independent and dependent variables, we can conclude that an increase in the value of the independent variable is associated with an increase in the value of the dependent variable.

True or False

Q7. The standard error of the estimate is the sample estimated standard deviation of the explanatory variable (X).

True or False

Q8. The sample estimate of the variance of error in a Regression model is

a. MSE

b. b0

c. b1

d. SSE

e. SSxy