A friend has told you that his multiple regression has a high R-squared but all the estimates of the regression slopes are insignificantly different from zero on the basis of t tests of significance. This has probably happened because the Group of answer choices Explanatory variables are highly colinear Explanatory variables are not correlated Dependent variable does not change much Error term is heteroscedastic Error term is autocorrelated

A friend has told you that his multiple regression has a high R-squared but all the estimates of the regression slopes are insignificantly different from zero on the basis of t tests of significance. This has probably happened because the Group of answer choices Explanatory variables are highly colinear Explanatory variables are not correlated Dependent variable does not change much Error term is heteroscedastic Error term is autocorrelated

College Algebra

7th Edition

ISBN:9781305115545

Author:James Stewart, Lothar Redlin, Saleem Watson

Publisher:James Stewart, Lothar Redlin, Saleem Watson

Chapter1: Equations And Graphs

Section: Chapter Questions

Problem 10T: Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s...

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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 scientific foundation wanted to evaluate the relation between y= salary of researcher (in thousands of dollars), x1= number of years of experience, x2= an index of publication quality, x3=sex (M=1, F=0) and x4= an index of success in obtaining grant support. A sample of 35 randomly selected researchers was used to fit the multiple regression model. Parts of the computer output appear below. The p-value of the ANOVA F test will be very large, since it's clear that all of the variables are good predictors of salary very small, since it's clear that all of the variables are good predictors of salary very large, since it's clear that none of the variables are good predictors of salary very small, since it's clear that none of the variables are good predictors of salary
True or false (Explain why.): A school administrator is running a regression of fall quarter final grades (Y ) on undergraduate grades (X). Since he only has data on graduate students, he does not have people who performed poorly in their undergraduate studies. His sample is therefore nonrandom (selection on X) and her estimates will be biased. True or false (Explain why): Because the IV estimator uses only a subset of the variation in an explanatory variable, precision always increases when compared to OLS.
True or false (Explain why.): A school administrator is running a regression of fall quarter final grades (Y ) on undergraduate grades (X). Since he only has data on graduate students, he does not have people who performed poorly in their undergraduate studies. His sample is therefore nonrandom (selection on X) and her estimates will be biased.
IS the following statment true or false, please explain why For each x term in the multiple regression equation, the corresponding β is referred to as a partial regression coefficient.
A college decides to carry out a study on the time spent on video games and GPA earned. Surprisingly, this shows a moderate and positive correlation. Suppose a student is at the 25th percentile of both time spent on video games and GPA earned. Relative to all students at the 25th percentile of time spent on video games, this means that the student's GPA is Group of answer choices higher than we'd expect from the regression relationship about what we'd expect from the regression relationship lower than we'd expect from the regression relationship No answer text provided.
You will not obtain a high R-squared value in a multiple regression if all the partial slopecoefficients are individually statistically insignificant on the basis of the usual t test. State the reason. why?
A health researcher plans a research project in which they will do a multiple regression analysis and perform all the significance tests at α = 0.01. They expect a medium sized effect, f2 = 0.15. They have a candidate set of eight variables with which to perform the regression. What is the necessary sample size to achieve a power of 0.8?
Suppose you would like to estimate Y= B1 + B2 X + B3 Z + u model using data from 40 firms. Suppose you are to perform Breuch-Pagan (LM type test) for homoscedasticity, define the auxiliary regression? Further suppose that you find R-squared from the auxiliary regression to be 0.85, carry out B-P test for homoscedasticity at %5 level of significance and interpret the result (Set the hypotheses).
There exists a moderate relationship between the variables x and y.if we draw samples of increasing sample size,what can we expect from the sample r value,the regression slope and the p value of the regression or correlation be affected by increasing sample size
There are four conditions that should be at least approximately true for linear regression. A QQ plot of the residuals can be used to check which of the following conditions: 1. The distribution of the values of y at each value of x should be normal AND there should be no extreme outliers 2. A straight line is the best model to describe the association between x and y, AND the variance of the values of y at each value of x should be the same 3. The distribution of the values of y at each value of x should be normal AND a straight line is the best model to describe the association between x and y
If the R-squared for a regression model relating the outcome y to an explanatory variable x is 0.9. This implies that y and x are positively correlated.