Discuss the cause of Heteroskedasticity in regression analysis
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Q: (a) Determine the probability P (7 or more).
A: here given n = 8 p =0.7 q = 1 - p = 1 - 0.7 = 0.3
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?What does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?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?
- Is this statement true "In a nonlinear regression, the slope of the population regression function depends on the value of one or more of the independent variables" if Yes, explain How?4. True or False? Multiple logistic regression analysis applies when there is a single dichotomous outcome and more than one independent variable.1. Sue is conducting a regression analysis to predict the amount of salaries expense using the number of employees and the average rate of pay. This type of regression analysis is called a(n) independent regression. linear regression. multiple regression. dependent regression.
- 1.How is the slope coefficient (b1) in a simple linear regression different than the coefficient (b1) in a multiple linear regression model? 2. When would you use a logistic regression model? 3.What is the appropriate statistical test to assess whether there is an association between obesity status (normal weight, overweight, obese) and 5-year incident cardiovascular disease (CVD)? Suppose each participant’s obesity status (category) is known as is whether they develop CVD over the next 5 years or not. *PLEASE INCLUDE TABLE OF THIS5. True or False? “Linear regression models are of no use when fitting polynomials and other non-linear patterns observed in the data." Explain.Illustrate the Regression Discontinuity Estimators?
- Explain the Theory of Linear Regression with One Regressor?Discuss the usefulness of regression.We want to predict the probability of car accidents based on three risk factors: (i) average driving speed, (ii) weather, and (iii) user age. What is the most appropriate machine learning model for this case? Why? a. Linear regression b. Logistic regression c. K-means clustering
