Using the regression table I created, how should I perform a T-test for the predictors and assuming the Normality, Homoscedasticity, Independence of observations are satisfied? ## Regression Analysis### Regression Statistics- **Multiple R**: 0.9915- **R Square**: 0.9830- **Adjusted R Square**: 0.9824- **Standard Error**: 108.8113- **Observations**: 61### ANOVA (Analysis of Variance)| | **df** | **SS** | **MS** | **F** | **Significance F** ||----------|--------|------------------|-------------------|------------|--------------------|| Regression | 2 | 39731441.7245 | 19865720.8622 | 1677.8619 | 0.0000 || Residual | 58 | 686714.3411 | 11839.9024 | | || Total | 60 | 40418156.0656 | | | |### Coefficients Analysis| | **Coefficients** | **Standard Error** | **t Stat** | **P-value** | **Lower 95%** | **Upper 95%** ||----------------|------------------|--------------------|------------|-------------|---------------|---------------|| Intercept | -90.2166 | 113.1013 | -0.7977 | 0.4283 | -316.6134 | 136.1802 || Asking Price | 9.2169 | 0.1716 | 53.7184 | 0.0000 | 8.8735 | 9.5604 || Age | 2.5069 | 0.8994 | 2.7873 | 0.0072 | 0.7065 | 4.3073 |### Calculations- **b2, b1, b0 Intercepts**: 2.5069, 9.2169, -90.2166- **b2, b1, b0 Standard Error**: 0.8994, 0.1716, 113.1013- **R Square, Standard Error**: 0.9830, 108.8113

It is required to describe the procedure of performing t-tests for the predictors, assuming that the…

Answered: Using the regression table I created,…

Using the regression table I created, how should I perform a T-test for the predictors and assuming the Normality, Homoscedasticity, Independence of observations are satisfied?

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

On the first statistics exam, the coefficient of determination between the hours studied and the grade earned was 80%. The standard error of estimate was 10. There were 15 students in the class. Develop an ANOVA table for the regression analysis of hours studied as a predictor of the grade earned on the first statistics exam. (Round your DF answers to nearest whole number and other answers to 2 places.) Source DF SS MS Regression 1 Error Total 13 14
Based on the results of the regression, what would be the mose likely conclusion?
Explain the concept of Asymptotic Distribution of the OLS Estimatorand t-Statistic in the multi regression model?
Please help interpret this SPSS output of a multiple regression analysis result? DV- To what extent the product safety incident have changed your perceptions of the involved brand(s) IV'S- Trustworthy , Reliability , I don’t know how good the company’s products will be before I buy it. , Preventability
The attached results are for a multiple regression study of smartphone addiction (SSA-SV) proneness in relation to 1) Gender 2)Age 3) Anxiety (GAD-7). I just want to clarify that age is statistically significant with p = 0.006; is this correct? What's throwing me off is the notation "< .001" on the top line under the p category. I was under the impression that the p-value would need to be less than 0.001.
A car dealership would like to develop a regression model that would predict the number of cars sold per month by a dealership employee based on theemployee's number of years of sales experience. The accompanying regression output was developed based on a random sample of employees. ANOVA df SS Regression 1 79.909407 Residual 23 261.210593 Total 24 341.12 Coefficients Standard Error Intercept 7.271539 1.229763 Slope 0.539854 0.203521 The coefficient of determination is 0.234 Test statistic= 0.704 P-value= 0.014 Construct a 95% confidence interval around the sample slope and interpret its meaning. The confidence interval is (__________,_________). (Type an integer or decimal rounded to three decimal places as needed.)
In a regression analysis, three independent variables are used in the equation based on a sample of 47 observations. In the ANOVA table for a multiple regression analysis, what are the degrees of freedom associated with the F-statistic? Multiple Choice 3 and 46 4 and 47 3 and 43 2 and 46
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…
A researcher is interested in whether an approved supplement enhances the performance of baseball players. The research compares two different baseball teams on the number of home runs they hit for the season. Which test is most appropriate to conduct? Chi-square Independent t-test Correlation/Regression Dependent t-test One-Way ANOVA
What are the different measures used for the OLS estimate of the multiple regression line?
Police sometimes use footprint evidence to estimate the height of a suspect. Data was collected from 36 randomly selected men in Nebraska in 2001. The regression model assumptions have been checked, and they are all satisfied. We want to test if there is a positive linear association between shoe print size and average height. The p-value of the appropriate test was found to be 0.0006. (a) Give your brief conclusion. Note that no significance level is provided. (b) Give your conclusion in the context of the problem. (This question will be marked manually by your instructor).
d. Present major regression summary outputs for both regression lines showing: regression statistics, coefficients, standard error, t stats, p-values and 95% confidence interval.