A researcher would like to predict the dependent variable Y from the two independent variables X1 and X2 for a sample of N = 12 subjects. Use multiple linear regression to calculate the coefficient of multiple determination and test statistics to assess the significance of the regression model and partial slopes. Use a significance level a = 0.02. X1 X2 38.8 50.1 24.7 25.2 42.8 56.6 45.9 33.2 72.8 20.8 43.9 61.5 46.2 36.5 40.9 44.8 47.4 25.4 38.9 49 35.3 23.2 55 28.8 44.7 44.1 40 49.1 55.8 24.5 40.4 52.6 20 52.1 48.6 44.9 This data set can be downloaded as a *.csv file: Download CSV. R F = P-value for overall model = t1 for b1, P-value = t = for bz, P-value = What is your conclusion for the overall regression model (also called the omnibus test)? O The overall regression model is statistically significant at a = 0.02. O The overall regression model is not statistically significant at a = 0.02. Which of the regression coefficients are statistically different from zero? O neither regression coefficient is statistically significant O the slope for the first variable bị is the only statistically significant coefficient O the slope for the second variable bz is the only statistically significant coefficient

A researcher would like to predict the dependent variable Y from the two independent variables X1 and X2 for a sample of N = 12 subjects. Use multiple linear regression to calculate the coefficient of multiple determination and test statistics to assess the significance of the regression model and partial slopes. Use a significance level a = 0.02. X1 X2 38.8 50.1 24.7 25.2 42.8 56.6 45.9 33.2 72.8 20.8 43.9 61.5 46.2 36.5 40.9 44.8 47.4 25.4 38.9 49 35.3 23.2 55 28.8 44.7 44.1 40 49.1 55.8 24.5 40.4 52.6 20 52.1 48.6 44.9 This data set can be downloaded as a *.csv file: Download CSV. R F = P-value for overall model = t1 for b1, P-value = t = for bz, P-value = What is your conclusion for the overall regression model (also called the omnibus test)? O The overall regression model is statistically significant at a = 0.02. O The overall regression model is not statistically significant at a = 0.02. Which of the regression coefficients are statistically different from zero? O neither regression coefficient is statistically significant O the slope for the first variable bị is the only statistically significant coefficient O the slope for the second variable bz is the only statistically significant coefficient

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

See similar textbooks

Similar questions

Interpret the estimated education coefficient. Is the estimate of the constant statistically significant at the 5% level? Explain how you reached this conclusion. Imagine you want to test with an F-test whether the effect of married and nonwhite are jointly significantly different from zero. Write down the null and alternative hypothesis for such a test
A researcher would like to predict the dependent variable Y from the two independent variables X1 and X2 for a sample of N = 15 subjects. Use multiple linear regression to calculate the coefficient of multiple determination and test the significance of the overall regression model. Use a significance level a = 0.01. X1 X2 Y 38.4 58.8 48.2 63.4 47.9 55.6 48.4 54.6 33.1 54.9 48.7 47.4 54.8 54.2 51.7 44.1 78.6 64.8 55.3 48 38.6 56.8 54.3 34.1 56.5 61 42.6 52.1 49.2 35.8 57.5 49.4 51.2 55.3 66.7 56.7 57.5 53.5 25.6 71.8 64.4 63.3 29.1 62.8 56.7 Sreg SS.res R F P-value =
Answer it correctly and explain well.Typed answer only. Do it fast.
A researcher would like to predict the dependent variable Y from the two independent variables X1 and X2 for a sample of N=15 subjects. Use multiple linear regression to calculate the coefficient of multiple determination and test the significance of the overall regression model. Use a significance level α=0.01. X1X1 X2X2 YY 44.5 64.2 39.3 27.4 58.2 18.8 37.6 74 40.2 40.5 12.1 73.3 33.4 60.8 15.5 0.3 21.7 27.4 91.4 57 69.8 56.4 58.9 98.4 30.8 46.8 40 54 83.2 31.5 31.6 66.2 29.8 37.5 57.1 46.7 55.3 38.7 99.8 66 61.2 84.1 53.7 37.9 45.9 SSreg=SSres=R2=F= P-value =
A researcher would like to predict the dependent variable Y from the two independent variables X1 and X2 for a sample of N = 12 subjects. Use multiple linear regression to calculate the coefficient of multiple determination and test statistics to assess the significance of the regression model and partial slopes. Use a significance level a = 0.01. X1 X2 53.2 50.8 61.2 91.9 84.6 66.8 62 57.8 61.9 46.4 43 70.1 59.1 65.5 56.5 72.6 61.7 62.7 69.5 70.4 63.7 70.9 70.6 64.9 68.6 61.5 61.1 54.7 57 49 34.6 43.9 45 67.2 This data set can be downloaded as a *.csv file: Download CSV. 41.6 44.4 R F = P-value for overall model = ti = for b1, P-value = tą = for b2, P-value = What is your conclusion for the overall regression model (also called the omnibus test)? O The overall regression model is statistically significant at a = 0.01. O The overall regression model is not statistically significant at a = 0.01. Which of the regression coefficients are statistically different from zero? O neither…
Write the formula for the estimated regression line and interpret the slope of the estimated regression line, the intercept of the estimated regression line- Is it meaningful?, and the estimated R2. Based on the fitted regression model, what is the predicted ATST for a child who is 7 years old? What is the correlation between AGE and ATST? Does the residual plot suggest that the fitted regression line is inappropriate for these data? Explain why or why not. Suppose that a new subject is added to the study data and that subject is 12.5 years old with an ATST of 580 minutes. If the regression model were to be refit with this additional data point, would the new slope be greater than or less than -14.041? Justify your response.
Let x be the weight of a car (in hundreds of pounds), and let y be the miles per gallon (mpg). Suppose a car weighs 3800 pounds. What does the data forecast for the miles per gallon expected? x= 27 44 32 47 23 40 34 52 y= 30 19 24 13 29 17 21 14 State the correlation coefficient and state the regression lin equation.
The money raised and spent (both in millions of dollars) by all congressional campaigns for 8 recent 2-year periods are shown in the table. The equation of the regression line is y = 0.942x +27.609. Find the standard error of estimate s, and interpret the result. 793.9 1042.3 957.7 1203.3 450.7 673.7 745.1 778.6 Money raised, x Money spent, y 734.8 1024.2 929.1 1160.6 448.6 697.9 735.7 751.2 Find the standard error of estimate s, and interpret the result. (Round to three decimal places as needed.) How can the standard error of estimate be interpreted? O A. The standard error of estimate of the money raised for a specific amount of money spent is about s, million dollars. O B. The standard error of estimate of the money spent for a specific amount of money raised is about s, million dollars.
Prev The table below gives the list price and the number of bids received for five randomly selected items sold through online auctions. Using this data, consider the equation of the regression line, y = bo + b₁x, for predicting the number of bids an Item will receive based on the list price. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, In practice, It would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Price in Dollars 28 33 36 42 45 Number of Bids 1 7 8 9 10 Step 3 of 6: Find the estimated value of y when x = 33. Round your answer to three decimal places. Table Copy Data Next
A researcher would like to predict the dependent variable YY from the two independent variables X1 and X2 for a sample of N=13 subjects. Use multiple linear regression to calculate the coefficient of multiple determination and test statistics to assess the significance of the regression model and partial slopes. Use a significance level α=0.01. X1 X2 Y 38.3 52.7 55.5 50.9 76 89.3 33.5 57.6 18.6 40.9 43.6 27.7 48.7 63.5 76.5 49.6 73.3 57.4 36.9 53.3 29.8 35.4 62.8 50.2 39 76.3 65.4 64.9 57.7 71.5 54.8 58 51.5 37.8 62.6 54.7 56.7 50.5 36.6 R2=F= P-value for overall model = t1=for b1, P-value = t2= for b2, P-value =
Prev The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, y = bo + b₁x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, In practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age Bone Density 61 62 68 69 40 357 350 343 340 315 Step 1 of 6: Find the estimated slope. Round your answer to three decimal places. Table Copy Data Next
a ift = The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, bo + b₁x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, In practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. tab ** Answer How to enter your answer (opens in new window) Step 2 of 6: Find the estimated y-Intercept. Round your answer to three decimal places. esc 1945 ! 1 q alt a Z ebook x360 ng from any angle. @ 2 W S →>> X # 3 e d C $ 4 C r f Age Bone Density 359 % 5 V t g 36 51 63 66 70 357 328 314 310 Oll A 6 b y hp h & 7 O n u j * 8 N O i m ( 9 k O 100- 4 Tables ctrl { [ Keypad Keyboard Shortcuts Previous step answers Submit Answer D + = 11 : 90 ; ? Copy Data O SEAR Dec 2 Table ] USE YOUR SMARTPHONE FOR…