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Questivil 13 You calculated the below regression model at a 95% confidence level with 20 observations...
Consider the following Excel outout for a regression model where Y = GDP, X, employment and Xx = fixed capital Sample size = 20 observations Intercept Standard Error 34370.0541 5.8749 0.0962 Coefficients 59450 2848 12.3387 0.4346 Pour 0.1064 Star 17049 2.1003 Lower 95% -133019.7674 -0.0562 Upper 95% 14118.9979 2 4.7336 00003 Model 1: Y = Bo+B.X1+B2X:+8 Based on the value of statistic, determine whether you should reject or not to reject the null hypothesis of two failed test). Make decision...
2) Suppose the regression model y = B0 + B1x1 + B2x2 + B3x3 + B4x1x2 + B5x1x3 + B6x2x3 was fit to n = 27 data points with SSE = 2000.0. a) Set up the null and alternative hypotheses for testing whether the interaction terms are significant. b) Give the reduced model necessary to test the significance of the interaction terms. c) The reduced model resulted in SSE = 2800. Calculate the value of the test statistic appropriate for...
2) Suppose the regression model y = B0 + B1x1 + B2x2 + B3x3 + B4x1x2 + B5x1x3 + B6x2x3 was fit to n = 27 data points with SSE = 2000.0. a) Set up the null and alternative hypotheses for testing whether the interaction terms are significant. b) Give the reduced model necessary to test the significance of the interaction terms. c) The reduced model resulted in SSE = 2800. Calculate the value of the test statistic appropriate for...
Will rate, thank you in advance. A researcher developed a regression model to predict the tear rating of a bag of coffee based on the plate gap in bag-sealing equipment. Data were collected on 32 bags in which the plate gap was varied. An analysis of variance from the regression showed that by = 0.7427 and Son = 0.2396. a. At the 0.05 level of significance, is there evidence of a linear relationship between the plate gap of the bag-sealing...
1) Determine the critical value for a 95% confidence interval shown below (95% confidence you will be below 2). 2) Determine the critical value for a 95% confidence interval shown below (95% confidence you will be above 2). 0
J. Thie uala set is 1or b4 banks. R2 Std. Error 6.977 0.519 64 ANOVA table Source df MS F p-value 1 3,260.0981 66.97 1.90E-11 62 3,260.0981 3,018.3339 Regression Residual 48.6828 Total 6,278.4320 63 Regression output Confidence Interval Lower 95% Upper 95% variables Coefficients Std. Error tStt p-value Intercept 65763 1.9254 3.416 0011 2.727510.4252 X1 00452 0.0055 8.183 1.90E-11 0.0342 0.0563 Calculate the R2 a. b. In words what does the R? say about total revenue for a bank? c....
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...
Given below are four observations collected in a regression study on two variables x (independent variable) and y (dependent variable). *NOOO a. Develop the least squares estimated regression equation. b. At 95% confidence, perform at test and determine whether or not the slope is significantly different from zero. C. Perform an F test to determine whether or not the model is significant. Let a = 0.05. d. Compute the coefficient of determination.
In estimating a regression based on monthly observations from January 1987 to December 2002 inclusive, you find that the coefficient on the independent variable is positive and significant at the 0.05 level. You are concerned, however, that the t−statistic on the independent variable may be inflated because of serial correlation between the error terms. Therefore, you examine the Durbin-Watson statistic, which is 1.8953 for this regression. Perform a statistical test to determine if serial correlation is present. Assume that the...
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...