Consider the results in Table 5. After running the regression, we test whether thevariables onwer and hhinc are jointly statistically significant at 5%. The value of theF-statistic is 323.27. Note that the sample size is 1,593. What is the outcome of thetest? Would it be correct to reject the null hypothesis if either the t-statistic for hhincor the t-statistic for owner exceeded 1.96 in absolute value? Explain. The questions below are based on a dataset containing the characteristics of 5,407households. In particular, we will use the following variables:- size: home size, measured in square feet.- hhinc: annual household net income, measured in euros.- owner. dummy variable equal to 1 if the living space is owned, and 0 if the livingspace is rented.- hhsize1: dummy variable equal to 1 if the number of household's members is 1 or2, and 0 otherwise.hhsize2: dummy variable equal to 1 if the number of household's members is 3 or4, and 0 otherwise.hhsize3: dummy variable equal to 1 if the number of household's members is 5 orabove 5, and 0 otherwise.- edu: education level of household's members.The Appendix contains tables with the critical values of the standard normal distribution andthe F distribution. Table 5. regress size hhinc owner hhsizel hhsizez hhsize3, robust noconstantLinear regressionNunber of obs1,593F(5, 1588)3895.70Prob > F0.0000R-squared0.9255Root MSE353.16RobustsizeCoefficient std. err.tP>|t|(95% conf. interval)hhinc6.80 0.000.00456700067170032495.0058845owner404.7925442.6217hhsizel675.808624.2422227.88 0.00628.2585723.3587hhsize2788.660636.4762821.62717.1138860.2073hhsize)993.660958.6329416.95e.000878.65481108.667

Null Hypothesis: H0: Owner and hhinc are not jointly statistically significant. Alternative…

Consider the results in Table 5. After running the regression, we test whether the variables onwer and hhinc are jointly statistically significant at 5%. The value of the F-statistic is 323.27. Note that the sample size is 1,593. What is the outcome of the test? Would it be correct to reject the null h

Consider the results in Table 5. After running the regression, we test whether the variables onwer and hhinc are jointly statistically significant at 5%. The value of the F-statistic is 323.27. Note that the sample size is 1,593. What is the outcome of the test? Would it be correct to reject the null h

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

Consider the following Stata regression output (some values are deliberately removed). Variable | Obs Mean Std. Dev. Min Маx lwage points | rebounds | assists 269 6.952296 .8813761 5.010635 8.655214 269 10.21041 5.900667 1.2 29.8 269 4.401115 2.892573 2.092986 .5 17.3 269 269 2.408922 1682.193 12.6 3533 minutes | 893.3278 33 Source | SS df MS Number of obs F(, Prob > F Model | Residual | = R-squared Adj R-squared Root MSE %3D 0.4146 Total | lwage | Сoef. Std. Err. P>|t| [95% Conf. Interval .0795364 points rebounds .0277761 .0637763 .0204514 3.12 0.002 0.252 0.227 -.0230647 -.0000747 .087425 .0003133 assists .0321805 .0280576 1.15 minutes .0001193 .0000985 1.21 _cons Answer the following questions. Please round your answers to 2 decimal places. Model SS : ; Residual S : ; Total SS :
Based on the results of the regression, what would be the mose likely conclusion?
One group of accounting students took a distance learning class, while another group took the same course in a traditional classroom. At α = .10, is there a significant difference in the mean scores listed below? Exam Scores for Accounting Students Statistic Distance Classroom Mean scores x¯1x¯1 = 9.7 x¯2x¯2 = 10.0 Sample std. dev. s1 = 2.7 s2 = 2.9 Number of students n1 = 23 n2 = 23 Specify the decision rule. (Round your answers to 3 decimal places. A negative value should be indicated by a minus sign.) Find the test statistic tcalc. (Round your answer to 4 decimal places. A negative value should be indicated by a minus sign.) Use Excel to find the p-value. (Round your answer to 3 decimal places.)
Use the following ANOVA table for regression to answer the questions. Analysis of Variance Source DF SS MS F P Regression 1 291.4 291.4 2.01 0.158 Residual Error 174 25230.0 145.0 Total 175 25521.4 Give the F-statistic and p-value.Enter the exact answers.The F-statistic is =The p-value is =
The following data relate to marks in Advanced Accounts and Business Statistics in B.Com. (H.), Il yr Examination of a particular year in Delhi University : Mean Marks in Advanced Accounts Mean Marks in Business Statistics Standard Deviation of Marks in Advanced Accounts Standard Deviation of Marks in Business Statistics Coefficient of Correlation between the Marks in Advanced Accounts and Business Statistics Find the two regression lines and calculate the expected marks in Advanced Accounts if the marks secured by a student in Business Statistics are 40. = 30 = 35 = 10 = 7 = 0-8
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)
Hi, please help with this assignment. Please show the work step by step as I am having trouble understanding how to compute them.
Step 1 of 3. State the null and alternative hypotheses for the test. Step 2 of 3. Compute the value of the test statistic. Round your answer to three decimal places Step 3 of 3. Draw a conclusion and interpret the decision.
Let's study the relationship between brand, camera resolution, and internal storage capacity on the price of smartphones. Use α = .05 to perform a regression analysis of the Smartphones01CS dataset, and then answer the following questions. When you copy and paste output from MegaStat to answer a question, remember to choose to "Keep Formatting" to paste the text. a. Did you find any evidence of multicollinearity and variance inflation among the predictors. Explain your answer using a VIF analysis. b. Copy and paste the normal probability plot for your analysis. Is there any evidence that the errors are not normally distributed? Explain. c. Copy and paste the Residuals vs. Predicted Y-values. Does the pattern support the null hypothesis of constant variance for the errors? Explain. d. Study the residuals analysis. Which observations, if any, have unusual residuals? e. Study the residuals analysis. Calculate the leverage statistic. Which observations, if any, are high leverage…
5.
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.
Answer the Question 1. In multiple regression: a. the ANOVA table tells us whether the three main regression coefficients (R, R-square, adjusted R-square) are significantly different from 1. .50 2. 1.00 3. Zero 4. 1.50 b. the adjusted R-square can be interpreted as 1. Th percentage of variance accounted for in the dependent variable by the set of independent variables 2. The percentage of variance accounted for in the dependent variable by the set of independent variables minus an estimate penalty 3. The percentage of variance accounted for in the dependent variable by a single independent variable 4. The strength of a relationship between the dependent variable and the set of independent variables