4. In the expressionPr(deny = 1|P/I Ratio, black) = (-2.26 +2.74P/I ratio + 0.71black),the effect of increasing the P/I ratio from 0.3 to 0.4 for a white persona. is 0.274 percentage points.b. is 6.1 percentage points.c. should not be interpreted without knowledge of the regression R².d. is 2.74 percentage points.5. Omitting relevant regressors from the model results in OLS estimators that are:a. biased but more precise.b. are both unbiased and more efficient.c. both biased and less efficient.d. None of the above

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Answered: 5. Omitting relevant regressors from…

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section4.6: Regression And Median-fit Lines

Problem 4GP

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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?
A set of n = 15 pairs of X and Y values has a correlation of r = +0.80 with SSY = 75, and the regression equation for predicting Y is computed. Find the standard error of estimate for the regression equation. How big would the standard error be if the sample size were n = 30.
If a sample of 25 pairs of data yields a correlation coefficient, r, of 0.390 and the scatterplot displays a linear trend, can you use the regression equation to make predictions, assuming your x-values are within the domain of the data set? Choose your answer from the multiple choice answers below A.) Yes, because rcrit = 0.396 and the regression coefficient, r, is less than this value. B.) Yes, because rcrit = 0.381 and the regression coefficient, r, is greater than this value. C.) No, because rcrit = 0.381 and the regression coefficient, r, is greater than this value. D.) No, because rcrit = 0.396 and the regression coefficient, r, is less than this value.
The above plot: a) reveals sure evidence that the population slope is unequal to 0 b) reveals sure evidence that the sample slope is unequal to 0 c) can be used alone to reject the null hypothesisthat the population slope is unequal to 0 d) can be used alone to reject the null hypothesis that the population slope is equal to 0 e) a and c f) a and d
Which of the following statements is NOT true? a.If the correlation coefficent, rr, is negative, then the slope of the regression line must always be negative. b.For variables x and y, the value of the correlation coefficent will not change c.if the units of x and y are changed, (i.e., if both x and y are changed from say inches to meters) d.If r≠0r≠0 , then a significant linear correlation will exist between the two variables e.The value of the correlation coefficient must be within the interval: −1≤r≤1
What is the effect of this violation on the regression model? "The number of observations n is less than or equal to the number of parameters to be estimated"
The following table shows the marks in statistics and economics for ten students. Fit a least square line to the data using a) ‘X’ as the independent variable b) What will be the regression equation if X= 20
Consider the following sample regression equation yˆ = 150 − 20x, where y is the demand for Product A (in 1,000s) and x is the price of the product (in $). The slope coefficient indicates that if _____
If the correlation between X and Y is zero A. r squared would be 1 B. r squared would be zero C. The variance accounted for by X in Y would be 1 D. The slope of the regression line would be 1

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5. Omitting relevant regressors from the model results in OLS estimators that are: a. biased but more precise. b. are both unbiased and more efficient. c. both biased and less efficient. d. None of the above