3. Using the attached data set (or CPS08 from the textbook Empirical Exercise E4.1), run aregression of average hourly earnings (AHE) on Age and carry out the following exercise:a. Is the estimated regression slope coefficient statistically significant (or, can you reject the nullhypothesis Ho: B₁ = 0 versus a two-sided alternative at the 5% significance level? What is thep-value associated with coefficient's t-statistics?b. Construct a 95% confidence interval for the slope coefficient.SUMMARY OUTPUTRegression StatisticsMultiple R0.17036366R Square0.02902378Adjusted R Sq 0.02889782Standard Erro 9.99186151Observations7711ANOVARegressionResidualTotaldfSSMSFSignificance F1 23005.7375 23005.7375 230.432297 2.6346E-517709 769645.718 99.83729647710 792651.456Lower 95.0% Upper 95.0%Coefficients Standard Error t Stat1.08227522 1.18425524 0.91388679P-value Lower 95% Upper 95%0.36080492 -1.2391869 3.40373732 -1.2391869 3.40373732InterceptX Variable 1 0.60498629 0.03985418 15.1799966 2.6346E-51 0.52686127 0.68311131 0.52686127 0.68311131

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Answered: a. Is the estimated regression slope…

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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A local real estate agent argues that house prices in Pittsburgh are related tothe number of rooms in a house. You collect a random sample of 190 houses and run asimple regression using House Price (measured in dollars) as the dependent variableand Rooms (measured as the number of rooms in a house) as the independentvariable. Given below is the Excel output of the regression results. (a) Construct the 99.7% confidence interval for the slope of the regressionline.(b) Consider a house with 5 room. What is the probability that the housewill sell for more than $270,245?(c) A savvy real estate investor, Noah, owns a house in Pittsburgh thathe is planning to sell. Based on the regression put, Noah decides to destroy somewalls to reduce the number of rooms in the house, hoping to increase the houseselling price. Based on the regression output, do you think this is a good decision?Justify your comment.
Researchers are examining the relationship between hours of sleep and athletic performance among college athletes. Athletic performance will be measured on a numeric scale, with greater numbers indicating better performance. The researchers expect that the more hours the athletes sleep, the better they will perform. Assuming all conditions for inference are met, the researchers will create a 95 percent confidence interval for the slope of the regression line for predicting athletic performance from amount of sleep. For which of the following would the confidence interval support the researchers' expectations? (A) The confidence interval includes only positive values. (B) The confidence interval includes only negative values. (C) The confidence interval has a width less than 1. (D) The confidence interval has a width greater than 1. (E) The confidence interval includes the value 0.
a. b. C. Name: 3. You have been provided the following regression summery output for the demand for Good X. F df Significance F 0.00000798529 53.29202 Regression Residual Total Intercept Price (Px) Income (1) Price Other (Py) 3 56 59 Coefficients 355.8130 -4.9835 0.8762 -1.4893 SS 824.897 209.662 1,034.559 Standard Error 0.632473 0.939474 0.487969 0.968633 MS 255.3953 4.792375 P-value 6.45E-05 0.001985 0.078924 0.027889 Using the estimates above, state the demand function rounded to two decimals (Format: Qx=do+a1 Px + a ₂1+ a 3Py): Is the product called X a normal or inferior good? (motivate) Is the "Price Other (Py)" referring to a complement or substitute good (motivate)
(d) At the 0.05 level of significance, is there evidence of a linear relationship between the number of cases delivered and the delivery time? (e) Construct a 95% confidence interval estimate of the population slope β1. Interpret the confidence interval estimate. (f) How useful do you think this regression model is for predicting the delivery times?
Select all statements that are true of the least-squares regression line. ) It assumes a linear relationship between the explanatory and the response variable. R-squared is the portion of sample variance in the explanatory variable that can be explained by variation in the response variable. ) It can be used to predict the mean response of the explanatory variable. | R-squared is the portion of sample variance in the y variable that can be explained by variation in the x variable.
The value obtained for the test statistic, z, in a one-mean z-test is given. Also given is whether the test is two tailed, left tailed, or right tailed. Also is given the P-value.A left-tailed test: z = -1.17 P-value: 0.1210 Use technology to create a scatter plot of the data from the previous question. Include the regression line. (Hand drawn graphs will not be accepted.) The explanatory (input) variable and the response (output) variable must be clearly labeled, within the context of this problem.
For a given set of x and y data values, assume that the regression model assumptions are valid and that a 90% confidence interval for ₁ is given by (-2.2, -0.1). Which of the following statements are true? i) At a = 0.10, there is a significant linear relationship between x and y. ii) In the scatterplot of x and y, the values of y tend to decrease as the values of x increase. iii) Based on this confidence interval, we would reject the null hypothesis of no linear relationship at any significance level a ≤ 0.1. Select one: a. i) O b. i) and ii) O c. ii) d. i), ii), and iii)
Suppose that x and y are two variables of a population and that the assumptions for regression inferences are met with x as the predictor variable and y as the response variable. a. What statistic is used to estimate the slope of the population regression line? b. What statistic is used to estimate the y-intercept of the population regression line? c. What statistic is used to estimate the common conditional standard deviation of the response variable corresponding to fixed values of the predictor variable?

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