5. Considered the linear regression Table for Advertising data:

Linear Regression

Coefficient Std. error t-statistic p-value

Intercept 2.339 0.3119 9.42 < 0.0001

TV 0.046 0.0014 32.81 < 0.0001

radio 0.229 0.0086 21.89 < 0.0001

newspaper 0.00 1 0.0059 0.18 0.8599

Note that the input variables are measured in $1,000, whereas output in the thousands of items.

(a) Formulate null and alternative hypothesis about significance of the linear relationship between spending to TV advertisement and sales. Formulate your conclusions.

(b) Formulate null and alternative hypothesis about significance of the linear relationship between spending to newspaper advertisement and sales. Formulate your conclusions.

(c) Interpret the value of coefficient ₂, estimated coefficient for radio.

(d) Interpret the intercept coefficient.

(e) From the regression Table we know that the value of F statistics for this model was 570 and corresponding value of p = 0.0023. State the hypotheses about the overall significance of the regression and formulate your conclusion.