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3) (Total: 12 points) The results of the regression model is shown below. Using the p-value...
3. The following is a regression output for estimated visitors to Raging Waters, a water amusement park. Coefficients Error t Stat P-value 45.61 1.99 -2.38 Intercept Temperature Ticket Price 84.9...
3. The following is a regression output for estimated visitors to Raging Waters, a water amusement park. Coefficients Error t Stat P-value 45.61 1.99 -2.38 Intercept Temperature Ticket Price 84.998 2.391 0.4086 1.863 1.200 0.000 0.051 0.020 ANOVA MS 38.954 9.414 77.907 583.693 661.600 4.14 0.021 Residual Total 62 64 Write the regression equation. a. b. Conduct a global test of hypothesis (F-test) to see if any of the regression coefficients could be different from zero at the 5% significance...
please help! Following is a simple linear regression model: y = a + A + &...
please help!
Following is a simple linear regression model: y = a + A + & The following results were obtained from some statistical software. R2 = 0.523 Syx (regression standard error) = 3.028 n (total observations) = 41 Significance level = 0.05 = 5% Variable Interecpt Slope of X Parameter Estimate 0.519 -0.707 Std. Err. of Parameter Est 0.132 0.239 Note: For all the calculated numbers, keep three decimals. Write the fitted model (5 points) 2. Make a prediction...
[8] A simple regression was performed using data on 50 states in USA. The variables were...
[8] A simple regression was performed using data on 50 states in USA. The variables were Y = current value of capital building (millions of dollars) and X = total debt held by each state bank (millions of dollars). Use α=0.01 Variables Coefficients Standard error Intercept Debt b0 = 478.54 b1 = 2.80 Sb0 = 19.43 Sb1 = 0.79 a) Use the degree of freedom (df=n-2 =48) for the t-test and find the two-tailed critical value for t by using...
Question 3 (3 points) The table below shows the regression results when calculating the least squares...
Question 3 (3 points) The table below shows the regression results when calculating the least squares line of regression relating variable x (predictor) to variable y (response): Intercept Coefficients 0.083 1.417 Standard Error 3.56 0.63 t Star 0.02 2.25 P-value 0.9822 0.0745 Does variable x share a statistically significant linear relationship with variable y at the 5% significance level? Yes, since the p-value of 0.0745 is greater than 0.05. Yes, since the slope coefficient of 1.417 is less than the...
A regression model relating 3, number of salespersons at a branch office, to y, annual sales...
A regression model relating 3, number of salespersons at a branch office, to y, annual sales at the office in thousands of dollars) provided the following computer output from a regression analysis of the data. Where ntotal = 32. ANOVA df MSF Significance F SS 6863.5 Regression Residual Total 9342.6 Stat P-value Intercept Number of Salespersons Coefficients 88.0 54.0 Standard Errort 12.175 5.865 a. Write the estimated regression equation (to whole number). y= Xx b. Compute the F statistic and...
5. Summary of regression between a dependent variable y and two independent variables X, and x2...
5. Summary of regression between a dependent variable y and two independent variables X, and x2 is as follows. Please complete the table: SUMMARY OUTPUT Regression Statistics Multiple R 0.9620 R Square R2E? Adjusted R Square 0.9043 Standard Error 12.7096 Observations 10 ANOVA F Significance F F=? Overall p-value=? Regression Residual Total 2 df of SSE MS MSR=? MSE? 14052.1550 1130.7450 SSTE? MSE? 9 Coefficients -18.3683 Standard Error 17.9715 t Stat -1.0221 Intercept ty=? 2.0102 4.7378 0.2471 0.9484 P-value 0.3408...
Regression Statistics Multiple R 0.6906 R Square 0.4769 Adjusted R Square 0.4705 Standard Error 7.4823 Observations...
Regression Statistics Multiple R 0.6906 R Square 0.4769 Adjusted R Square 0.4705 Standard Error 7.4823 Observations 83 Coefficients Standard Error t Stat P-value Intercept 50.5266 1.3369 37.7950 0.0000 Age 0.2087 0.0243 **** 0.0000 The Excel output above is from a regression of body length on age in a sample of bears. Use the output to answer the following questions. What is the value of b0? (1 dp) Answer What is the value of b1? (4 dp) Answer What is the se(b1)? (4dp) Answer...
For a simple linear regression results shown below, the P-value for the slope coefficient is as...
For a simple linear regression results shown below, the P-value for the slope coefficient is as follows: a hypothesis test of whether the regression coefficient ß1 is zero. a measure that determines if the linearity assumption is satisfied a hypothesis test of whether the regression coefficient for Advertising is equal to 6.738. the variability of the observed Y-values from the predicted values.
A regression analysis is performed using data for 36 single-family homes to predict appraised value (in...
A regression analysis is performed using data for 36
single-family homes to predict appraised value (in thousands of
dollars) based on land area of the property (in acres), X1i, and
age (in years), X2i, in month i. Use the results below to
complete parts (a) and (b) below.
Variable
Coefficient
Standard Error
t Statistic
p-value
Intercept
392.60372
51.68272
7.60
0.0000
Area, X1
451.43475
100.48497
4.49
0.0001
Age,X2
−2.17162
0.79077
−2.75
0.0097
a. Construct a 95% confidence interval estimate...
For a simple linear regression results shown below, the P-value for the slope coefficient is as...
For a simple linear regression results shown below, the P-value for the slope coefficient is as follows: A) a hypothesis test of whether the regression coefficient ß1 is zero. B) a measure that determines if the linearity assumption is satisfied C) a hypothesis test of whether the regression coefficient for Advertising is equal to 6.738. D) the variability of the observed Y-values from the predicted values.
3. The following is a regression output for estimated visitors to Raging Waters, a water amusement park. Coefficients Error t Stat P-value 45.61 1.99 -2.38 Intercept Temperature Ticket Price 84.998 2.391 0.4086 1.863 1.200 0.000 0.051 0.020 ANOVA MS 38.954 9.414 77.907 583.693 661.600 4.14 0.021 Residual Total 62 64 Write the regression equation. a. b. Conduct a global test of hypothesis (F-test) to see if any of the regression coefficients could be different from zero at the 5% significance...
please help!
Following is a simple linear regression model: y = a + A + & The following results were obtained from some statistical software. R2 = 0.523 Syx (regression standard error) = 3.028 n (total observations) = 41 Significance level = 0.05 = 5% Variable Interecpt Slope of X Parameter Estimate 0.519 -0.707 Std. Err. of Parameter Est 0.132 0.239 Note: For all the calculated numbers, keep three decimals. Write the fitted model (5 points) 2. Make a prediction...
Question 3 (3 points) The table below shows the regression results when calculating the least squares line of regression relating variable x (predictor) to variable y (response): Intercept Coefficients 0.083 1.417 Standard Error 3.56 0.63 t Star 0.02 2.25 P-value 0.9822 0.0745 Does variable x share a statistically significant linear relationship with variable y at the 5% significance level? Yes, since the p-value of 0.0745 is greater than 0.05. Yes, since the slope coefficient of 1.417 is less than the...
A regression model relating 3, number of salespersons at a branch office, to y, annual sales at the office in thousands of dollars) provided the following computer output from a regression analysis of the data. Where ntotal = 32. ANOVA df MSF Significance F SS 6863.5 Regression Residual Total 9342.6 Stat P-value Intercept Number of Salespersons Coefficients 88.0 54.0 Standard Errort 12.175 5.865 a. Write the estimated regression equation (to whole number). y= Xx b. Compute the F statistic and...
5. Summary of regression between a dependent variable y and two independent variables X, and x2 is as follows. Please complete the table: SUMMARY OUTPUT Regression Statistics Multiple R 0.9620 R Square R2E? Adjusted R Square 0.9043 Standard Error 12.7096 Observations 10 ANOVA F Significance F F=? Overall p-value=? Regression Residual Total 2 df of SSE MS MSR=? MSE? 14052.1550 1130.7450 SSTE? MSE? 9 Coefficients -18.3683 Standard Error 17.9715 t Stat -1.0221 Intercept ty=? 2.0102 4.7378 0.2471 0.9484 P-value 0.3408...
A regression analysis is performed using data for 36
single-family homes to predict appraised value (in thousands of
dollars) based on land area of the property (in acres), X1i, and
age (in years), X2i, in month i. Use the results below to
complete parts (a) and (b) below.
Variable
Coefficient
Standard Error
t Statistic
p-value
Intercept
392.60372
51.68272
7.60
0.0000
Area, X1
451.43475
100.48497
4.49
0.0001
Age,X2
−2.17162
0.79077
−2.75
0.0097
a. Construct a 95% confidence interval estimate...
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