Discuss the cause of Heteroskedasticity in regression analysis
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Discuss the cause of Heteroskedasticity in
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- Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?Table 2 shows a recent graduate’s credit card balance each month after graduation. a. Use exponential regression to fit a model to these data. b. If spending continues at this rate, what will the graduate’s credit card debt be one year after graduating?Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to 2012. a. Let x represent time in years starting with x=0 for the year 1997. Let y represent the number of seals in thousands. Use logistic regression to fit a model to these data. b. Use the model to predict the seal population for the year 2020. c. To the nearest whole number, what is the limiting value of this model?
- In regression analysis, what is the main problem caused by heteroskedasticity? Discuss first the nature of hetersokedasticity (explain what that is using an example) and then explain what problem it causes.Suppose this regression suffers from heteroskedasticity. How would you adjust the model to account for it?What is the connection between cointegration and spurious regression?
- Why Stochastic error term must be present in a regression equation?What is the justification for using bayesian binary logistic regression model in a research?What are homoskedasticity and heteroskedasticity in multiple linear regression? How would you check for heteroskedasticity in a multiple linear regression model?
- Explain the time series regression model assumptions?In logistic regression, the predictors are dichotomous, and the outcome is a continuous variable.Q3 Part (A) Where investment (I), government expenditure (G), and gross domestic product (Y) are measured in US$ billion and ̂u is the regression residualIs there any problem of Hetroscedasticity in above model? How do you know?
