2. One topic from this module is heteroskedasticity. A. Convince me that you know what heteroskedasticity is. B. How can you use a scatterplot of the residuals from a regression model to look for heteroskedasticity? C. Explain briefly how to conduct a Park test for heteroskedasticity.
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2. One topic from this module is heteroskedasticity.
A. Convince me that you know what heteroskedasticity is.
B. How can you use a scatterplot of the residuals from a regression model to look for heteroskedasticity?
C. Explain briefly how to conduct a Park test for heteroskedasticity.
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- Imagine you are trying to explain the effect of square footage on home sale prices in the United States. You collect a random sample of 100,000 homes that recently sold. a) Homes can be one of three types: single-family houses, townhomes, or condos. How would you control for a home’s type in a regression model? b) Write down a regression model that includes controls for home type, square footage, and number of bedrooms. c) How would you interpret the es3mated coefficients for each of the variables from part b? Be specific.Discuss and explain each of the assumptions of the simple linear regression model.You are the owner of a restaurant located in a beach resort in Hawaii and want to use regression analysis to estimate the demand for your fresh seafood dinners. You have collected data on the daily quantity of seafood dinners sold over the last summer season. In order to correctly specify your regression equation, which of the following variables should be considered? Select one: A. the prices charged for souvenirs in local stores B. the prices charged for scuba diving excursions at the resort C. the wages paid to your chef and servers D. the daily number of vacationers at the resort
- What is Regression Model in econometrics?Suppose you run a regression with quantity as your dependent variable and advertising as one of your independent variables. The p-value on advertising is .08. The marketing team is arguing that their advertising efforts are impacting sales, but the finance/economics department is arguing that there isn't evidence that the advertising is impacting sales. What side would you take and why?Suppose you run a regression with quantity as your dependent variable and advertising as one of your independent variables. The p-value on advertising is .08. The marketing team is arguing that their advertising efforts are impacting sales, but the finance/economics department is arguing that there isn't evidence that the advertising is impacting sales. What side would you take and why? Note that this question squarely hits the idea that stats is part science/part art...
- 1. Can you estimate a regression model for Y and X? 2. What are the assumptions of the model in 1? 3. Do you think that this model is accurate? 4. What are the related hypotheses of 37 5. Discuss and interpret your results. Y 4 4 -1 -2 11 -2 -4 0. 3. 7. 12 -3 -6 7. 14Which one of the following is NOT an assumption of the classical linear regression model (CLRM)? Select one: a. The disturbance terms are independent of one another. b. The dependent variable is not correlated with the disturbance terms. c. The explanatory variables are uncorrelated with the error terms. d. The disturbance terms have zero mean.Define Interpretation of coefficients in polynomial regression models?
- What is a linear regression model? What is measured by the coefficients ofa linear regression model? What is the ordinary least squares estimator?Define coefficients of the Linear Regression Model?1. The following model is a simplified version of the multiple regression model used by Biddle and Hamermesh (1990) to study the tradeoff between time spent sleeping and working and to look at other factors affecting sleep: sleep = Bo + Bitotwrk + Bzeduc + Bzage + u where sleep and totwrk (total work) are measured in minutes per week and educ and age are measured in years. (a) If adults trade off sleep for work, what is the sign of 1? (b) What signs do you think 2 and 3 will have? (c) Would you say totwrk, educ, and age explain much of the variation in sleep? What other factors might affect the time spent sleeping? Are these likely to be correlated with totwrk?