The following table was generated from the sample data of 10 junior high students regarding the average number of hours they are unsupervised per night, the average number of hours they play video games per night, and their final grades in their math class. The dependent variable is the final grade, the first independent variable (x1) is the number of hours unsupervised each night, and the second independent variable (2) is the number of hours of video games each night. Coefficients Standard Error 1-Stat p-value Intercept Hours Unsupervised 60.829438 3.861884 15.751235 0.000001 3.451483 0.826485 4.176100 0.004157 Hours Playing Video Games 4.918683 0.867336 5.671022 0.000758 Step 2 of 2: Indicate if any of the independent variables could be eliminated at the 0.05 level of significance. Answer O Keep all variables Copy Data Tables Keypad Keyboard Shortcuts

The following data was collected to explore how a student's age and GPA affect the number of parking tickets they receive in a given year. The dependent variable is the number of parking tickets, the first independent variable (1) is the student's age, and the second independent variable (x2) is the student's GPA. Effects on Number of Parking Tickets Age GPA Number of Tickets 17 2 1 17 2 2 18 2 4 20 2 5 20 3 5 22 3 6 233 22 3 6 3 7 25 4 7 Copy Data Step 2 of 2: Determine if a statistically significant linear relationship exists between the independent and dependent variables at the 0.01 level of significance. If the relationship is statistically significant, identify the multiple regression equation that best fits the data, rounding the answers to three decimal places. Otherwise, indicate that there is not enough evidence to show that the relationship is statistically significant. Answer How to enter your answer (opens in new window) Selecting a checkbox will replace the entered answer…

The following table was generated from the sample data of 10 college students regarding the number of parking tickets the student receives in a semester, the student's age, and the student's GPA. The dependent variable is the student's GPA, the first independent variable (x1) is the number of parking tickets, and the second independent variable (x2) is the student's age. Coefficients Standard Error 1-Stat p-value Intercept Number of Parking Tickets Student's Age 15.034003 -0.026275 -0.638331 1.302739 11.540305 0.000025 0.030254 0.062922 -0.868470 0.418515 -10.144838 0.000053 Copy Data Step 2 of 2: Indicate if any of the independent variables could be eliminated at the 0.05 level of significance. Answer x1 x2 Keep all variables Tables Keypad Keyboard Shortcu

The following data was collected to explore how the number of square feet in a house, the number of bedrooms, and the age of the house affect the selling price of the house. The dependent variable is the selling price of the house, the first independent variable (x1) is the square footage, the second independent variable (x2) is the number of bedrooms, and the third independent variable (x3) is the age of the house. Effects on Selling Price of Houses Square Feet Number of Bedrooms Age Selling Price 2750 5 14 296600 2696 5 11 294400 2523 4 7 281400 2057 4 7 240600 1797 4 5 208600 1767 4 5 196400 1684 4 4 171900 1554 3 4 162800 1521 3 3 144900 Copy Data Step 2 of 2: Determine if a statistically significant linear relationship exists between the independent and dependent variables at the 0.01 level of significance. If the relationship is statistically significant, identify the multiple regression equation that best fits the data, rounding the answers to three decimal places. Otherwise,…