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- A group of scientists are interested in finding out whether the days of rainfall during the dry season could predict the magnitude of butterfly migration in the local area during wet season. Every year for twenty years, they count the total days of rainfall during the dry season preceding the migration and measure the number of butterflies migrating in the following wet season. Which type of statistical test should they use to analyze their data? (pearson's r correlation OR, simple regression equation)41Which statement is not correct for multiple regression model? When we interpret this categorical variable, we would say the change we observe when one switches from the reference category to the specific category. The reference category will not be displayed in our model results. If we include a categorical variable with more than two values (e.g., religion) as an independent variable, we want to include a dummy variable for all categories except for two. We can include more than two categorical variables in the model. The value of the independent variable not included in the model is called "reference category."
- For linear regression with one variable, the unpredicted portion of the Y-score variance (MS residual) has df = n - 2. True False Submit AnswerWhen testing for bl in a regression model, the null hypothesis (2-tailed) is b1=0. Why? O Then the alternative hypothesis can be b0=1 This indicates that bl=b2 This indicates that bl=b0 A change in x does not result in a change in yI have a doubt when it comes to this reasoning : Imagine I have a variable that is correlated to Y and to X1 in a linear regression model. If I ommit it it will result in Omitted Variable Bias but if I include it, would it result in perfect multicolinearity and therefore for example a solution is to include control variables ? Is this right ? Thanks.
- 32. What effect on the results of a regression does data that exhibits heteroscedasticity cause? Higher risk of type I error Lower risk of type I error Higher risk of type II errorYou plan to fit a regression model that will be used to predict first-year college GPA (FYGPA) from high-school GPA (HSGPA), ACT score (ACT), first-generation status (Yes or No), socioeconomic class (lower class, lower to middle class, middle to upper class, and upper class), and school type (public or private). What is the total number of estimated regression coefficients? If the sample size is n = 250 students, what are the degrees of freedom for the following sources of variation: Regression Error TotalSuppose that you perform a hypothesis test for the slope of the population regression line with the null hypothesis H0: β1 = 0 and the alternative hypothesis Ha: β1 ≠ 0. If you reject the null hypothesis, what can you say about the utility of the regression equation for making predictions?
- In this section we introduced a descriptive measure of the utility of the multiple linear regression equation for making predictions.a. Dene and interpret this descriptive measure.b. Identify the symbol used for this descriptive measure.Police sometimes use footprint evidence to estimate the height of a suspect. Data was collected from 36 randomly selected men in Nebraska in 2001. The regression model assumptions have been checked, and they are all satisfied. We want to test if there is a positive linear association between shoe print size and average height. The p-value of the appropriate test was found to be 0.0006. (a) Give your brief conclusion. Note that no significance level is provided. (b) Give your conclusion in the context of the problem. (This question will be marked manually by your instructor).Explain why all-subsets regression is considered superior to stepwise regression in selecting a regression equation.