Question

Theory Question 3: Suppose you are testing a regression model for the presence of heteroskedasticity and...

Theory Question 3:
Suppose you are testing a regression model for the presence of heteroskedasticity and the p-value is 0.00. Provide the null and alternative hypotheses, the rejection rule and interpret the result.
Suppose you are testing for serial correlation and using the Serial Correlation LM text where the p-value is 0.8415. Provide the null and alternative hypotheses, the rejection rule and interpret the result.

Homework Answers

Answer #1

Null hypothesis H0: There is no presence of heteroskedasticity in the regression model.

Alternative hypothesis Ha: There is presence of heteroskedasticity in the regression model.

Rejection rule: p-value < 0.05

Since p-value is less than 0.05 significance level, we reject null hypothesis H0 and conclude that there is significant evidence of presence of heteroskedasticity in the regression model.

Null hypothesis H0: There is no serial correlation in the regression model.

Alternative hypothesis Ha: There is presence of serial correlation in the regression model.

Rejection rule: p-value < 0.05

Since p-value is greater than 0.05 significance level, we fail to reject null hypothesis H0 and conclude that there is no significant evidence of presence of serial correlation in the regression model.

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
Question 1 Heteroskedasticity is a violation of which assumption of the multiple regression model? a) E(ei)...
Question 1 Heteroskedasticity is a violation of which assumption of the multiple regression model? a) E(ei) = 0 b) cov(ei, ej) = 0 where i≠j c) The values of each independent variable xik are not random d) var(ei) = σ2 Question 2 You have estimated a multiple regression model with 6 explanatory variables and an intercept from a sample with 46 observations. What is the critical value (or t-crit) if you want to perform a one-tailed t test at the...
You are interested in testing Chips Ahoy’s claim that bags of Chips Ahoy cookies contain more...
You are interested in testing Chips Ahoy’s claim that bags of Chips Ahoy cookies contain more than 1000 chips, on average. Suppose you have an SRS of 62 bags of cookies and find that the sample mean is 1022 chips. The sample standard deviation s is 94.2 chips. There are no outliers or signs of strong skew. (a) Check the conditions for inference. Are the data from an SRS? Are the sample size and distributional requirements met? Specify why or...
QUESTION 3 Suppose a study is conducted to find out how the cost of flying between...
QUESTION 3 Suppose a study is conducted to find out how the cost of flying between Brisbane and Sydney using Boeing 737 varies with the number of passengers. The table below presents the number of passengers and associated costs for a random sample of 15 flights between Brisbane and Sydney using Boeing 737. Number of passengers 71 63 66 68 48 73 50 81 50 92 56 80 55 67 84 Cost ($) 4480 4020 4420 4150 3800 4300 4090...
You may need to use the appropriate technology to answer this question. In a regression analysis...
You may need to use the appropriate technology to answer this question. In a regression analysis involving 27 observations, the following estimated regression equation was developed. ŷ = 25.2 + 5.5x1 For this estimated regression equation SST = 1,550 and SSE = 590. (a) At α = 0.05, test whether x1 is significant. State the null and alternative hypotheses. H0: β0 ≠ 0 Ha: β0 = 0 H0: β1 = 0 Ha: β1 ≠ 0    H0: β0 = 0 Ha:...
3.) Now, you are going to run the multivariable linear regression model you just created. For...
3.) Now, you are going to run the multivariable linear regression model you just created. For credit: Provide your model command and summary command below along with all the output for your model summary. Model1 <- lm(LifeExpect2017~HouseholdIncome + Diabetic + FoodInsecure + Uninsured + DrugOverdoseMortalityRate ) > summary(Model1) Call: lm(formula = LifeExpect2017 ~ HouseholdIncome + Diabetic + FoodInsecure + Uninsured + DrugOverdoseMortalityRate) Residuals: Min 1Q Median 3Q Max -5.4550 -0.8559 0.0309 0.8038 7.1801 Coefficients: Estimate Std. Error t value Pr(>|t|)...
You may need to use the appropriate technology to answer this question. In a regression analysis...
You may need to use the appropriate technology to answer this question. In a regression analysis involving 30 observations, the following estimated regression equation was obtained. ŷ = 17.6 + 3.8x1 − 2.3x2 + 7.6x3 + 2.7x4 For this estimated regression equation, SST = 1,835 and SSR = 1,790. (a) At α = 0.05, test the significance of the relationship among the variables. State the null and alternative hypotheses. H0: One or more of the parameters is not equal to...
3.) Now, you are going to run the multivariable linear regression model you just created. For...
3.) Now, you are going to run the multivariable linear regression model you just created. For credit: Provide your model command and summary command below along with all the output for your model summary. Model1 <- lm(LifeExpect2017~HouseholdIncome + Diabetic + FoodInsecure + Uninsured + DrugOverdoseMortalityRate ) > summary(Model1) Call: lm(formula = LifeExpect2017 ~ HouseholdIncome + Diabetic + FoodInsecure + Uninsured + DrugOverdoseMortalityRate) Residuals: Min 1Q Median 3Q Max -5.4550 -0.8559 0.0309 0.8038 7.1801 Coefficients: Estimate Std. Error t value Pr(>|t|)...
Suppose that you are testing the following hypotheses where the variance is unknown: H0 : µ...
Suppose that you are testing the following hypotheses where the variance is unknown: H0 : µ = 100 H0 : µ ≠ 100 The sample size is n 20. Find bounds on the P-value for the following values of the test statistic. a. t0 = 2.75 b. t0 = 1.86 c. t0 = -2.05 d. t0 = -1.86
As a manager, you have been provided the following regression summery output for a regression model...
As a manager, you have been provided the following regression summery output for a regression model of a new product. PLEASE PROVIDE STEP BY STEP INSTRUCTIONS TO SOLVE THIS. THANK YOU df SS MS F Significance F Regression 3 156.4823 52.16077 28.01892 0.000002177 Residual 26 48.4023 1.861627 Total 29 204.8846 Coefficients P-value Intercept 23.8163 9.24E-07 Price -0.3035 0.001925 Price other -0.342937 0.112442 Income 0.23406 0.033889 a. What is the percent risk of the coefficients really being zero? In other words,...
Suppose you run a regression containing observations for each of the 74 kinds of cars releasted...
Suppose you run a regression containing observations for each of the 74 kinds of cars releasted in 1978 in the United States, and you regress price (in dollars) on weight (in pounds). You get the following results: βˆ 0 is -6.71, with SE 1174.4. βˆ 1 (slope coefficient on weight) is 2.04 with SE .377. • (4 points) Say, in words, what the slope coefficient means in this case, without taking a stand on causality. • (5 points) Suppose I...
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT