a. Test the null hypothesis that the slope coeficient is 0 versus the altermative hypothesis of greater than zero using probability of Type leror equal to 0.10.RejectHo, There is sufficient evidence that the slope coefficient is greater than zero.Determine the two-sided 95% confidence interval.O (Round to two decimal places as needed.)Determine the two-sided 99% confidence interval.OD (Round to two decimal places as needed.)b. Test the null hypothesis that the slope coefficient is 0 versus the alternative hypothesis of greater than zero using probability of Type I error equal to 0.10.Ho. There isevidence that the slope coefficient is greater than zero.Determine the two-sided 95% confidence interval.OD (Round to two decimal places as needed.)Determine the two-sided 99% confidence interval.OD (Round to two decimal places as needed.)c. Test the null hypothesis that the slope coefficient is 0 versus the alternative hypothesis of greater than zero using probability of Type I error equal to 0.10.Ho. There isevidence that the slope coefficient is greater than zero.Determine the two-sided 95% confidence interval.OD (Round to two decimal places as needed.)Determine the two-sided 99% confidence interval.OD (Round to two decimal places as needed.)d. Test the null hypothesis that the slope coefficient is O versus the altemative hypothesis of greater than zero using probability of Type I error equal to 0.10.Ho. There isevidence that the slope coefficient is greater than zero.Determine the two-sided 95% confidence interval.OD (Round to two decimal places as needed.)Determine the two-sided 99% confidence interval.OD (Round to two decimal places as needed.) Given the simple regression model Y = Bo + B,X and the regression results that follow, test the null hypothesis that the slope coefficient is 0 versus the alternative hypothesis of greater than zero using probability of Type I error equal to 0.10, anddetermine the two-sided 95% and 99% confidence intervals.a. A random sample of size n= 39 with b,= 8 and= 2.9b. A random sample of size n = 49 with b, = 8.3 and= 2.9c. A random sample of sizen= 39 with b, = 5.3 and= 1.52%3Dd. A random sample of sizen=32 with b, = 9.5 and= 1.5...a. Test the null hypothesis that the slope coefficient is 0 versus the alternative hypothesis of greater than zero using probability of Type I error equal to 0.10.RejectHo. There is sufficientevidence that the slope coefficient is greater than zero.Determine the two-sided 95% confidence interval.( ) (Round to two decimal places as needed.)Determine the two-sided 99% confidence interval.(| ) (Round to two decimal places as needed.)

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Answered: Given the simple regression model Y =…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The given quantities below were calculated from a sample data set. Στο 338 I Lu=308 Ση2 = 4678 2 y = 4236 Determine the least squares regression line. Round values to four decimal places, if necessary. Σry = 3595 n = 30 Determine the correlation coefficient. Round the solution to four decimal places, if necessary.
17. Additional information was obtained from EXCEL. Conduct a test of hypothesis to determine if any of the regression coefficients do not equal 0 Use the 005 significance level. The regression equation is: Salary = 19.2 + 3.10 Years + 0.269 Perform - 0.704 Absent Intercept Years Perform Absent Coefficients Standard Error 19.186 3.096 0.269 -0.704 12.146 0.706 0.120 0.586 -1.202 t Stat 1.580 4.385 P-value 0.143 0.001 0.046 0.255 2.252 а. Но: H: Họ: H1: Họ: H1: b. The decision rules are to reject Ho if What is your decision? Interpret. c. 305 Multiple Regression and Correlation Analysis Chapter 14
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In the multiple regression model with a quarterback's salary the response variable Y and the X variables pass completion percentage (PCT), number of touchdowns (TD), and age; the test of joint significance rejected HO: beta1 = beta2 = beta3 = 0. What does that mean? O Most of these X variables are significant in explaining salary. O At least one of these X variables is significant in explaining salary. O Each of these X variables is significant in explaining salary. O The model with all three X variables is significantly better than using sample mean salary alone to estimate expected salary
The statsmodels ols() method is used on an exam scores dataset to fit a multiple regression model using Exam4 as the response variable. Exam1, Exam2, and Exam3 are used as predictor variables. The general form of this model is: If the level of significance, alpha, is 0.10, based on the output shown, is Exam1 statistically significant in the multiple regression model shown above? Select one. A text version of this output is available. OLS Regressin Results Dep. Variable: Model: Method: R-squar ed: Adj. R-squared: F-statistic: Prob (F-statistic): Log-Likelihood: AIC: 0.178 0.125 3.329 0.0276 -169.85 347.7 355.4 Exam4 OLS Date: Time: No. Observations: Least Squares Sun, 18 Aug 2019 10:59:12 Df Residuals: of Nodel: Covarianco Тура: 50 46 3 nonr obust BIC: Coef std err P>|t| [0.025 0.975) t Intercept Examl Exam2 Exam3 46.2612 0.1742 0.1462 0.0575 10.969 0.120 0.078 0.053 4.217 1.453 1.873 1.085 0.000 0.153 0.067 0.284 24.181 -0.067 -0.011 -0.049 68.341 0.416 0.303 0.164 Onnibus: 0.886 0.642…
Suppose that you have estimated coefficients for the regression model Y = B₁ + B₁X₁ + ß2X2 + ß3X3. Test the hypothesis that all three of the predictor variables are equal to 0, given the analysis of variance shown on the right. Use α = 0.05. Click here to view page 1 of a table of critical values of F. Click here to view page 2 of a table of critical values of F. Choose the correct null and alternartive hypotheses below. A. Ho: B₁ B₂ =B3 = 0 H₁: at least one ß; #0 C. Ho: B₁ B₂ = 3 = 0 H₁: B₁0, B₂0, B3 > 0 Find the critical value. The critical value is (Round to two decimal places as needed.) Source Regression Residual Error DF SS 3 9,654 23 2,400 B. Hō: at least one ß; ‡0 H₁: B₁ =B₂ =B3 = 0 D. H₁: B₁ = P₂ = ³3 = 0 H₁: B₁ B₂ B3 0 MS
To investigate the relationship between the selling price of a house, yy, in dollars, and the size of the house xx, in square feet, a local builder collected data on a random sample of 120 houses from a certain region. Assume that the conditions for inference for the slope of a regression line are met. The resulting 95 percent confidence interval for the population slope of the regression line relating price and size is given by (62,99). The local builder claims that the selling price of houses from the region increases by $104 for every extra square foot of space in the house. Which of the following best describes the conclusion that can be reached about this claim based on the confidence interval? A)The claim is supported by the interval, since the interval does not contain the value 0. B)The claim is supported by the interval, since all values in the interval are positive. C)The claim is supported by the interval, since the interval does not contain the…
I need assitance with how the answers in the table were conducted. And how to calculate the residuals uA and uB and add them to the table. SSR All Answers are provided and correct.
A Simple Linear Regression (SLR) was performed where the monthly Revenue ("Rev", the y-variable) was regressed on the monthly Advertising Expenditures ("Expend", the x-variable). Excel was used to construct the 98% Confidence Interval (CI) estimate of beta subscript 1. The Excel-generated Regression output is provided below: ANOVA df SS MS F Significance F Regression 1 492.528125 492.528125 10.65525634 0.046980871 Residual 3 138.671875 46.22395833 Total 4 631.2 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 98.0% Upper 98.0% Intercept 23.1328125 5.324310936 4.344752359 0.022510469 6.188478833 40.07714617 -1.043301388 47.30892639 Expend 3.1015625 0.950164031 3.264239014 0.046980871 0.077716489 6.125408511 -1.212850033 7.415975033 a. Enter the value of the Left-Hand Endpoint (LHEP) of the 98% Confidence Interval (CI) estimate of beta subscript 1. Round off your answer to the fourth decimal place. The LHEP of the 98% CI for…
The data from exercise 3 follow. xi 2 6 9 13 20 yi 7 18 9 26 23 The estimated regression equation is = 7.6 + .9x. What is the value of the standard error of the estimate (to 4 decimals)? What is the value of the t test statistic (to 2 decimals)? What is the p-value? Use Table 1 of Appendix B.Selectless than .01between .01 and .02between .02 and .05between .05 and .10between .10 and .20between .20 and .40greater than .40Item 3 What is your conclusion ( = .05)?SelectConclude a significant relationship exists between x and yCannot conclude a significant relationship exists between x and yItem 4 Use the F test to test for a significant relationship. Use = .05.Compute the value of the F test statistic (to 2 decimals). What is the p-value?Selectless than .01between .01 and .025between .025 and .05between .05 and .10greater than .10Item 6 What is your conclusion?SelectConclude a significant relationship exists between x and yCannot conclude a significant relationship exists…
Find the simple regression line y=α+βx for the pairs of points belonging to the independent and dependent variables (xi,yi) , respectively. Also, interpret the result by calculating the Pearson correlation coefficient. Please dont use excel.
Test the null hypothesis that the slope is zero versus the two-sided alternative in the following setting using the alpha = 0.05 significance level: n = 30, yhat = 30.8 + 2.1x, and SEb1 = 1.05.

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