Breusch-Pagan / Cook-Weisberg test for heteroskedasticityHo: Constant varianceVariables: fitted values of pricechi2 (1)Prob> chi2 ==20.550.0000OaWe have homoskedasticityO b The OLS standard errors are incorrect.OCWe fail to reject the null hypothesis so we have heteroskedasticity.Od. The parameter estimates are biased.

It is required to identify the correct option regarding the conclusion of the given test of…

Answered: Breusch-Pagan / Cook-Weisberg test for…

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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BUS – 173 (Applied Statistics) # Determining if the following statement are True and False. If False, write the correct statement. Also Solve the MCQ 01. In the Simple linear regression model, components of the random error term are assumed to be independent (a) True (b) False 02. The possible for the perfect negative correlation is +1 (a) True (b) False 03. The possible range of coefficient of determination (r^2) is -1 to 1 a) True (b) False 04. A scatter diagram is a - (a) two-dimensional graph of a straight line (b) two-dimensional graph of a curved line (c) two-dimensional graph of a data points (d) one-dimensional graph of randomly scattered data
Interpret the following regression equation with (UR) uemployment rate as dependent variable and (INF) inflation as the independent variable.
Which statement is not correct?A. Spurious correlation can often be reduced by expressing X and Y in per capita terms.B. Autocorrelation is mainly a concern if we are using time - series data.C. Heteroscedastic residuals will have roughly the same variance for any value of X.D. Standardized residuals make it easy to identify outliers or instances of poor fit. ( don't hand writing solution)
What happens when you overfit a regression model? Question 25 options: The model captures too much of the random variation in the sample data and fails to predict accurately for the population. The p-value for the F-test of overall significance is greater than 0.05. So many variables are added to the model that the Adjusted {"version":"1.1","math":"<math xmlns="http://www.w3.org/1998/Math/MathML"><msup><mi>R</mi><mn>2</mn></msup></math>"} value exceeds 1 None of the relationships in the model are found to be statistically significant.
Dependent Variable: CO2 Method: Least Squares Date: 04/20/17 Time: 09:46 Sample: 1990 2013 Included observations: 24 Variable Coefficient Std. Error t-Statistic Prob. C 2.002813 6.458672 0.310097 0.7597 GDP 0.022114 0.011872 1.862670 0.0773 ENERGY -0.734352 0.328388 -2.236233 0.0369 POP 0.203927 0.293686 0.694371 0.4954 R-squared 0.825079 Mean dependent var 3.625982 Adjusted R-squared 0.798841 S.D. dependent var 0.108170 S.E. of regression 0.048515 Akaike info criterion -3.062883 Sum squared resid 0.047074 Schwarz criterion -2.866541 Log likelihood 40.75460 Hannan-Quinn criter. -3.010793 F-statistic 31.44583 Durbin-Watson stat 1.410912 Prob(F-statistic) 0.000000 c-Write down the econometric model for the above estimation by d-using the information obtained from above table d-Write down the least…
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Q.No.1. (Marks 08) Explain the following with suitable examples. Mutually exclusive events Sampling Correlation Regression
The data in personalities is bivariate normally distributed Carry out a formal t-test for the association between extroversion and neuroticism in personalities H0: The population correlation coefficient is 0. HA: The population correlation coefficient is not 0. What is the value of the t-statistic corresponding to this test? Carry out a formal t-test for the association between extroversion and neuroticism in personalities. H0: The population correlation coefficient is 0. HA: The population correlation coefficient is not 0. What is the critical value of the t-statistic required to reject the null hypothesis at a confidence level of 0.05
13. STATEMENTS FIRST: CORRELATION CAN BE USED TO DETERMINE THE DEGREE OF RELATIONSHIP BETWEEN VARIABLES SECOND: COEFFICIENT CORRELATION RANGES FROM 0-1A. IF BOTH STATEMENTS ARE TRUEB. IF BOTH STATEMENTS ARE FALSEC. IF THE FIRST IS TRUE AND THE SECOND IS FALSED. IF THE FIRST IS FALSE AND THE SECOND IS TRUE 14. STATEMENTS FIRST; STANDARD DEVIATION IS THE SQUARE ROOT OF THE VARIANCE SECOND: DISPERSION GIVES US THE IDEA OF THE DEGREE OF SCATTERING OF THE DATA IN THE DISTRIBUTION A. IF BOTH STATEMENTS ARE TRUEB. IF BOTH STATEMENTS ARE FALSEC. IF THE FIRST IS TRUE AND THE SECOND IS FALSED. IF THE FIRST IS FALSE AND THE SECOND IS TRUE 15. CHARACTERISTICS OF THE NORMAL CURVEI. CURVE IS ASYMMETRICAL ABOUT MEANII. TAILS OF THE NORMAL CURVE ARE ASYMPTOTIC RELATIVE TO THE HORIZONTAL LINEIII. TOTAL AREA UNDER THE NORMAL CURVE IS EQUAL TO 1IV. NORMAL CURVE ARE SUBDIVIDED INTO THE THREE STANDARD DEVIATION A. I, II, AND III ONLYB. II, III, AND IV ONLYC. I, II, III, AND IVD. I, II, AND IV ONLYE. I,…
ont Paragraph Styles Editing -A professor from a Quantitative Methods in Business course decided to research the relationship between the Mid Term Exam, the average number of study hours spent per week during the semester and the final course grade for a given student. A sample of containing data from a previous semester was provided by the instructor and summarized in the following table: # of Students Mid-Term exam Study hours per Final course grade week grade 1 50.0 2.0 65.0 60.0 4.0 85.0 55.0 3.5 75.0 4 85.0 6.0 90.0 55.0 5.0 70.0 6. 72.0 4.5 89.0 7 75.0 6.5 91.0 8 45.0 3.0 65.0 6. 88.0 5.5 89.0 10 90.0 7.5 96.0 Develop a linear regression model, where Y is the Final Grade Course and X is the Mid-Term Exam. Calculate the coefficient of determination (r 2 , the coefficient of correlation (r), the variance (o 2) for Text Predictions: On
Which of the following are true? (Select all that apply.) 1 An assumption of a linear regression is a consistent dispersion of the observations from the regression line. 2 An assumption of a linear regression is that the residuals form a normal distribution. 3 Omitted variable bias is when you don’t include the dependent variable.
1:49 AA O www-awn.aleks.com : d on the same scale from a population, O REGRESSION AND CORRELATION Linear relationship and the.. y u V 1.0 3.0 1.0 7.2 11 10 10 9- 84 2.0 | 4.4 2.0 9.0 3.0 | 3.0 3.0 | 7.0 4.0 4.9 4.0 5.6 6- 5.0 4.3 5.0 8.1 4. 4- 6.0 | 7.0 6.0 4.8 2. 7.0 | 6.1 7.0 4.3 8.0 7.8 8.0 | 7.1 9.0 | 7.0 Figure 1 9.0 6.0 Figure 2 10.0 8.3 10.0 4.3 t mn w 1.0 10.0 1 10- x 9- 1.0 3.8 11 2.0 | 5.8 10- 94 2.0 9.0 3.0 | 8.1 3.0 | 8.0 7 4.0 7.0 4.0 | 9.2 6- 5. 5.0 10.3 4. 5.0 6.0 4- 3 3 6.0 9.7 6.0 5.0 2. 7.0 | 9.8 7.0 | 4.0 8.0 | 7.9 8.0 3.0 9.0 2.0 Figure 4 |10.0 1.0 9.0 | 6.6 Figure 3 10.0 3.7 Answer the following questions. The same response answer for more than one question. 1. Which data set has an apparent negative, but not perfect, linear relationship between its two variables? Choose one 2. In which data set is there evidence of a strong nonlinear relationship between the two variables? Choose one 3. Which data set indicates the strongest negative linear Choose one relationship…

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