hown below is a portion of a computer output for regression analysis relating y (dependent variable) and x (independent variable). ANOVA   df SS Regression 1 24.061 Residual 10 67.979   Coefficients Standard Error Intercept 11.064 2.049 x −0.566 0.301 (a) What has been the sample size for the above regression analysis?

Data on 17 randomly selected athletes was obtained concerning their cardiovascular fitness (measured by time to exhaustion running on a treadmill) and performance in a 20-km ski race. Both variables were measured in minutes and a regression analysis was performed. ski = 86 2.4 treadmill Coefficients Estimate (Intercept) Treadmill 86 -2.4 Std. Error What is the test statistic? -2.791 0.26 0.86 Is there sufficient evidence to conclude that there is a linear relationship between cardiovascular fitness and ski race performance? Round your answers to three decimal places. Using your answer from the previous question, find the p-value. Part 2 of 3

What mean physical health score would you expect in a group of 28-year-old women with a graduate degree?

The commercial division of a real estate firm is conducting a regression analysis of the relationship between x, annual gross rents (in thousands of dollars), and y, selling price (in thousands of dollars) apartment buildings. Data were collected on several properties recently sold and the following computer output was obtained. ANOVA df MS F Significance F Regression 1. 41587.2 Residual 7 Total 8 51984.7 Coefficients Standard Error t Stat p-value Intercept 20.000 3.2213 6.21 Annual Gross 7.280 1.3621 5.29 Rents a. How many apartment buildings were in the sample? b. Write the estimated regression equation (to 2 decimals if necessary). = + c. Use the t statistic to test the significance of the relationship at a 0.05 level of significance. What is the p-value? Use Table 2 of Appendix B. p-value is - Select your answer What is your conclusion? Select your answer - d. Use the F statistic to test the significance of the relationship at a 0.05 level of significance. Compute the F test…

A student used multiple regression analysis to study how family spending (y) is influenced by income (x1), family size (x2), and additions to savings (x3). The variables y, x1, and x3 are measured in thousands of dollars. The following results were obtained. ANOVA       df SS Regression 3 45.9634 Residual 11 2.6218 Total         Coefficients Standard Error intercept 0.0136   x1 0.7992 0.074 x2 0.2280 0.190 x3 -0.5796 0.920 answer please : 1: Carry out a test to see if x3 and y are significantly related. Use a 5% level of significance.

Observations are taken on sales of a certain mountain bike in 30 sporting goods stores. The regression model was Y= total sales (thousands of dollars), X₁ = display floor space (square meters). X₂ competitors' advertising expenditures (thousands of dollars), X3 = advertised price (dollars per unit). Predictor Intercept FloorSpace Competing Ads Price Coefficient 1,287.26 11.52 -6.934 -0.1476 (a) Write the fitted regression equation. (Round your coefficient Competing Ads to 3 decimal places, coefficient Price to 4 decimal places, and other values to 2 decimal places. Negative values should be indicated by a minus sign.) ý= 1,287 26 + 11:52 *FloorSpace + (6.934) CompetingAds + (0.1446) * Price

A student used multiple regression analysis to study how family spending (y) is influenced by income (x) family size (x2), and addition to savings(x3). The variables y, x1, and x3. The variables y, x1, and x3 are measured in thousands of dollars . The following results were obtained.       ANOVA        df SS Regression 3 45.9634 Residual 11 2.6218 Total         Coefficient Standard Error Intercept 0.0136   X1 0.7992 0.074 X2 0.2280 0.190 X3 -0.5796 0.920   Write out the estimated regression equation for the relationship between the variables. Compute coefficient of determination. What can you say about the strength of this relationship? Carry out a test to determine whether y is significantly related to the independent variables. Use a 5% level of significant. Carry out a test to see if X3 and y are significantly related. Use a 5% level of significance

The ANOVA summary table to the right is for a multiple regression model with six independent variables. Complete parts (a) through (e). Draw a conclusion. Choose the correct answer below. (3) Degrees of Source Freedom Regression Error Total 6 26 32 Sum of Squares 240 190 430 A. There is insufficient evidence of a significant linear relationship with at least one of the independent variables because the test statistic is less than the critical value. O B. There is sufficient evidence of a significant linear relationship with at least one of the independent variables because the p-value is less than the level of significance. C. There is sufficient evidence of a significant linear relationship with at least one of the independent variables because the test statistic is greater than the level of significance. D. There is insufficient evidence of a significant linear relationship with at least one of the independent variables because the test statistic is greater than the critical value.

Waterbury Insurance Company wants to study the relationship between the amount of fire damage and the distance between the burning house and the neorest fire station. This information will be used in setting rates for insurance coverage. For o somple of 30 claims for the last year, the director of the actuarial department determined the distance from the fire station (x) and the amount of fire domage, in thousands of dollars (y). ANOVA table Source Regression Residual SS df MS F 1,870.5782 1,870.5782 41.39 1,265.4934 3,136.0716 28 45.1962 Total 29 Regression output Standard Variables Coefficients Error t(df-28) Intercept Distance-X 13.76815 3.106 2.914 3.77es e. 5861 6.43 Click here for the Excel Data File a-1. Determine the regression equation. (Round your answers to 3 decimal places.) y3D X. a-2 Is there a direct or indirect relotionship between the distance from the fire station and the amount of fire damage? The relationship between distance and damage is b. How much domage would…

A student used multiple regression analysis to study how family spending (y) is influenced by income (x1), family size (x2), and additions to savings(x3). The variables y, x1, and x3 are measured in thousands of dollars. The following results were obtained.   ANOVA                                   df                  SS Regression                3                   45.9634 Residual                  11                   2.6218 Total                                 Coefficients     Standard Error Intercept                0.0136 x1                          0.7992                   0.074 x2                          0.2280                   0.190 x3                         -0.5796                   0.920   Write out the estimated regression equation for the relationship between the variables.  Compute coefficient of determination. What can you say about the strength of this relationship?  Carry out a test to determine whether y is…