A regression analysis with formula y 30 • 2x has a standard error of 1, and a t-statistic of 2.0. The hypothesis being tested is: HO: B1 - 0; Ha: B1 / 0. What are the p-value and 90% oonfidence intervals for B1? OApvalue. 0.074; 90% C: (0.19, 3.81) Obpvalue 381, 00% C: (0.074,0.19) Ocpvalue: 0.19, 90% C (0.074, 3.81) Odpvalu 0.15, 90% C (024, 4.09)
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- Use the information from a simple linear regression given in the table below to calculate a 95% confidence interval for B1. SSXY = 285.2 SSXX = 23 S = 7 n = 15 Beta0 hat = 36 Betal hat = 12.4 O (25.78, 46.22) O (11.50, 13.29) O (- 9.67, 34.47) O (9.25, 15.55)After running a regression you conduct a hypothesis test of Ho: ß = 2.5 versus Hạ: B + 2.5 is performed using a = 0.10. The value of the test statistic z = -1.80 (the critical value is -1.645). If the true value of B is 2.5, does the conclusion you reach result in Type I, Type II error, or the correct decision? O Type II Error O Type I Error O correct decision not enough informationA simple linear regression model was created based on 25 samples. The 95% confidence interval for the estimate of B1 is (1.5, 4.6). Find the F-statistic for the model. Report your answer in 3 decimal places
- Fifty students take two midterm exams. On the first exam, the mean score is 65.0 and the standard deviation is 7.00. On the second exam, the mean score is 55.0 with a standard deviation of 10.00. The correlation coefficient of the two score is 0.70. Obtain the least squares regression line using the second exam score to predict the first exam score.4.2 A sample of 19 female bears was measured for chest girth (y) and neck girth (x), both in inches. The least squares regression equation relating the two variables is = 5.32 + 1.53 x. The standard deviation of the regression is s = 3.692. y^ 4.2.1 What is a 95% confidence interval for the average (or mean) chest girth for bears with a neck girth of 20 inches? The standard error of the fit is s.e.(fit) = 0.880 a. (27.9, 43.9) b. (28.1, 43.7) c. (34.1, 37.8) d. None of the above 4.2.2 Interpret the confidence interval obtained in 4.2.1Suppose that a sample of n = 12 pairs of X and Y scores has SSY = 90 and a Pearson correlation of r = +0.40. Does the regression equation predict a significant portion of the variance? Test with α = .05.(hint: SStotal = SSY; r2 = SSregression/SSTotal)
- The fish in my pond have mean length 14.73 inches with a standard deviation of 2.27 inches and mean weight 4.83 pounds with a standard deviation of .8 pounds. The correlation coefficient of length and weight is .6. If the length of a particular randomly selected fish is reported to be 17 inches, and if we use simple linear regression to predict the weight of a fish whose length is reported to be 15.8 inches long, then what is the expected squared error?A simple linear regression model was created based on 25 samples. The 95% confidence interval for the estimate of β1 is (1.5, 5.5). What is the t-statistic for β1? Report your answer in 3 decimal places.The regression output is reportedin Table 5. Calculate the standard error, t-statistic, p-value, and 95% confidenceinterval for the variable owner. Is the coefficient of owner statistically significant at5%?
- An analyst has used a sample of 100 observations to create a regression equation with one independent variable. The intercept coefficient is 2.1 with a standard error of 0.4. and the slope coefficient for the variance of the prediction error is 9. If the value of the independent variable is 5.0, the prediction interval for the dependent variable at a 95% confidence level is closest to? Is it? A. 1.1 to 37.1 B. 13.1 to 25.1 C. 14.2 to 24.0Which one(s) are true? I. Combination of high adjusted R2 and no statistically significant variables is an indication of multicollinearity II. Multicollinearity exists only in some regression models. III. With multicollinearity, it is possible for an F-test of overall significance to reject the null even though none of the individual t-tests do. IV. Correlation coefficient and VIF are two methods to detect multicollinearity. a. Il and III b. Il and IV c. I and III d. None e. I, III and IVThe slope of a regression line is 0.8, and the standard error of the slope is 0.3. The sample used to compute this regression line consisted of 12 participants. Compute the 95% confidence interval for the slope. Type the upper limit of the confidence interval?