Can I get some help!!!

#3. Below is output from a regression. The dependent variable is the number of cars sold. The independent variables are: GNP and the interaction variable GNPWhenUnhappy. That is, for certain time periods the sentiment of the country is 'unhappy'; GNPWhenUnhappy is equal to GNP for time periods when the country is unhappy and 0 when the country is happy. See partial data below. Call: 1m(formula = Sales ~ ., data = SalesWhenUnHappy) Residuals: Min 1Q Median 3Q -500.87 -172.70 -44.27 171.36 686.33 Max Coefficients : (Intercept) Estimate Std. Error t value Pr(> It!) GNP 1330. 05888 202. 49436 6. 568 4.02e-07 ** * 0. 33849 0. 05982 5. 659 4. 60e-06 * * * GNPWhenUnHappy -0. 01981 0. 03277 -0.605 0. 55 Signif. codes: 0 ***' 0. 001 **' 0.01 ' *' 0.05 .' 0.1 1 Residual standard error: 257.9 on 28 degrees of freedom Multiple R-squared: 0.5335, Adjusted R-squared: 0. 5002 F-statistic: 16.01 on 2 and 28 DF, p-value: 2. 311e-05 To the right of data table, sketch the regression relationship based on the output. Label all or any axes, slopes, intercepts or constant differences. Use all variables that are currently included in the regression. [10 points] GNPWhen Sales GNP UnHappy 2910 2640 0 2562 2595 0 2385 2701 0 2520 2785 2785 2142 2509 0 2130 2570 0 2190 2667 0 2370 2878 2878 2208 2835 0 2196 2897 0 1758 2744 0 1944 2582 2582 4. Define each of the following completely (including reference to the sample vs. the population where approp provide the notation for the term provided. [11 Points total] H (2 pts.): Sampling distribution (3 pts.): o (2 pts.): * (2 pts. ): Standard deviation of the sample (2 pts.)