The null hypothesis for testing for the presence of autocorrelation is Select one: a. the error terms are correlated over time. b. the error terms have constant variance over time. c. the error terms follow an AR(1) process. d. the error terms are not correlated over time.
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- Four Air Force trainee pilots take a test of visual acuity (higher scores mean better acuity) and an anxiety test (higher scores mean more anxiety. The scores are as follows: Person Acuity (x) Anxiety (y) 1 1 7 2 1 8 3 2 4 4 4 -1 Calculate critical value , SP the correlation coefficient and determine whether the correlation is statistically significant at the .05 significance level, two-tailedIt is false for DCA of fixed effects and random effects a. They are all true. b.In random effects the inference can be extended to treatments that are not experienced and in fixed effects it is not. c. The analysis of variance is performed on the variances for the random effects analysis and on the means for the fixed effects analysis. d. In both it is possible to choose for the factor both the number of levels and the levels why?Prof. Reed is interested in studying the determinants of fertility. She believes that women who report that they would like to have a higher number of children will actually have a higher fertility than women with low fertility ideals. The results from her analysis are based on the 2002 GSS. Calculate how much a woman's ideal fertility contributes to predict the variance of her actual number of children? Std. Mean Deviation Number of children 1.65 1.451 Ideal number of children 2.95 1.805 Pearson's r .144 Number of cases 211
- Let x represent the average annual salary of college and university professors (in thousands of dollars) in the United States. For all colleges and universities in the United States, the population variance of x is approximately o² = 47.1. However, a random sample of 17 colleges and universities in Kansas showed that x has a sample variance s² = 82.7. Use a 5% level of significance 1 test the claim that the variance for colleges and universities in Kansas is greater than 47.1. (a) What is the level of significance? State the null and alternate hypotheses. Ho: o²=47.1; H: o> 47.1 Ho: o²=47.1; H: o2 0.100 0.050 a, we fail to reject the null hypothesis. Since the P-value > x, we reject the null hypothesis. Since the P-values ∞, we reject the null hypothesis. Since the P-values a, we fail to reject the null hypothesis. (e) Interpret your conclusion in the context of the application. At the 5% level of significance, there is insufficient evidence to conclude the variance of annual salaries…Consider a regression analysis with n = 47 and three potential independent variables. Suppose that one of the independent variables has a correlation of 0.95 with the dependent variable. Does this imply that this independent variable will have a very large Student’s t statistic in the regression analysis with all three predictor variables?The weights (in pounds) of 6 vehicles and the variability of their braking distances (in feet) when stopping on a dry surface are shown in the table. Can you conclude that there is a significant linear correlation between vehicle weight and variability in braking distance on a dry surface? Use a =0.01. Welght, x Varlablity in braking distance, y 5960 5390 6500 5100 5870 4800 2 1.75 1.95 1.93 1.57 1.64 1.50 E Click here to view a table of critical values for Student's t-distribution. Setup the hypothesis for the test. Ho: P Vo Hạ: p Identify the critical value(s). Select the correct choice below and fill in any answer boxes within your choice. (Round to three decimal places as needed.) O A. The critical values are -to = and to = O B. The critical value is. Calculate the test statistic. t= (Round to three decimal places as needed.) What is your conclusion? a significant linear correlation between vehicle weight and variability in braking distance on a dry surface. There Venough evidence…
- The weights (in pounds) of 6 vehicles and the variability of their braking distances (in feet) when stopping on a dry surface are shown in the table. Can you conclude that there is a significant linear correlation between vehicle weight and variability in braking distance on a dry surface? Use α=0.01. Weight, x 5920 5370 6500 5100 5890 4800 Variability in 1.76 1.91 1.50 braking distance, y EEE Click here to view a table of critical values for Student's t-distribution. Setup the hypothesis for the test. Ho: P Ha: P 0 0 1.86 1.62 1.67 MWhich statement is not correct?A. Spurious correlation can often be reduced by expressing X and Y in per capita terms.B. Autocorrelation is mainly a concern if we are using time - series data.C. Heteroscedastic residuals will have roughly the same variance for any value of X.D. Standardized residuals make it easy to identify outliers or instances of poor fit. ( don't hand writing solution)Two coworkers commute from the same building. They are interested in whether or not there is any variation in the time it takes them to drive to work. They each record their times for 20 commutes. The first worker's times have a variance of 12.2. The second worker's times have a variance of 16.9. The first worker thinks that he is more consistent with his commute times and that his commute time is shorter. Test the claim at the 10% level.What is the F statistic? (Round your answer to two decimal places.)
- The data in personalities is bivariate normally distributed Carry out a formal t-test for the association between extroversion and neuroticism in personalities H0: The population correlation coefficient is 0. HA: The population correlation coefficient is not 0. What is the value of the t-statistic corresponding to this test? Carry out a formal t-test for the association between extroversion and neuroticism in personalities. H0: The population correlation coefficient is 0. HA: The population correlation coefficient is not 0. What is the critical value of the t-statistic required to reject the null hypothesis at a confidence level of 0.05Consider a regression analysis with n= 51 and four potential independent variables. Suppose that one of the independent variables has a correlation of 0.49 with the dependent variable. Does this imply that this independent variable will have a very small Student's t statistic in the regression analysis with all four predictor variables? Choose all that apply. A. The correlation between the independent variable and the dependent variable could result in a very small Student's t statistic as the correlation creates a high variance. B. Correlation between the independent variable and the dependent variable is not necessarily evidence of a small Student's t statistic. C. A high correlation among the independent variables could result in a very small Student's t statistic as the correlation increases the coefficient standard errors. D. Correlation between the independent variable and the dependent variable is evidence of a small Student's t statistic.Two coworkers commute from the same building. They are interested in whether or not there is any variation in the time it takes them to drive to work. They each record their times for 20 commutes. The first worker's times have a variance of 12.1. The second worker's times have a variance of 16.9. The first worker thinks that he is more consistent with his commute times and that his commute time is shorter. Test the claim at the 10% level. What is s1 in this problem? What is s2 in this problem?