Which of the following conditions can be detected from residual analysis? A) nonconstant variance B) multicollinearity...
Which of the following conditions can be detected from residual analysis?
|
A) nonconstant variance |
||
| B) |
multicollinearity |
|
| C) |
dummy variables |
|
| D) |
presence of transformations |
Homework Answers
Nonconstant variance is a condition which can be determined by using residual analysis.
Option A is correct.
Add Answer to:
Which of the following conditions can be detected from residual
analysis?
A) nonconstant variance
B)
multicollinearity...
What is multicollinearity and how does it affect the standard errors of OLS estimators? (b) In the context of perfect mu...
What is multicollinearity and how does it affect the standard errors of OLS estimators? (b) In the context of perfect multicollinearity between explanatory variables, explain why the OLS estimators cannot be derived. (c) With what methods can one detect multicollinearity? (d) Given relatively high variance of individual explanatory variables, explain why relatively low t-statistics but a relatively high F-statistic for the regression is an indication of multicollinearity.
1. Which of the following conditions will lead to a smaller variance for the intercept estimator...
1. Which of the following conditions will lead to a smaller variance for the intercept estimator for your multiple regression model? (A) X values cluster far from the origin of the X axis (B) X values closely pack around the mean of X in your sample (C) Small sample sizes (D) High correlation among the explanatory variables (E) Small error variance in the population regression function 2. R-squared (A) measures the proportion of variability of the dependent variable that is...
Question 5 1 pts Which of the following statements about multicollinearity are correct? Select all that...
Question 5 1 pts Which of the following statements about multicollinearity are correct? Select all that are correct. If you cannot justify dropping an explanatory variable the best solution to multicollinearity may be to do nothing Multicollinearity is a much more serious problem than omitted variable bias Getting better data is a good solution to multicollinearity Perfect multicollinearity can be detected in Minitab by attempting to run a regression. If the data is perfectly collinear the regression will not run...
Question 33 What does regression analysis attempt to establish? o a. multicollinearity o b. linearity in...
Question 33 What does regression analysis attempt to establish? o a. multicollinearity o b. linearity in the relationship between independent variables o c. a mathematical relationship between a dependent variable, for which future values will be forecast, and one or more independent variables with known values o d. linearity in the relationship between a dependent variable and a set of independent variables Question 34 How are states of nature assigned probabilities? oa. Use historical data. o b. Use best judgements....
4. The following is the output of linear regression analysis, which includes dummy variables and interactions....
4. The following is the output of linear regression analysis, which includes dummy variables and interactions. The following are the variables: Y = Birth weights of infants born in preterm in three hospitals (A, B and C) X = Gestation age in weeks flif infant was born in Hospital A 10 Otherwise s X2= flif infant was born in Hospital B 10 Otherwise Variable Coefficient Standard deviation 1 P (approximate) Constant -1.1361 4904 .07648 01523 .7433 .6388 X -.8239 .6298...
29. The following table shows the results of an analysis of variance comparing two treatment conditions...
29. The following table shows the results of an analysis of variance comparing two treatment conditions with a sample of n = 11 participants in each treatment. Note th several values are missing in the table. What is the missing value for MSwithin? ss dfMS Source Between xx xx 14 F=xx Within Total 154 xx C. 14 d. 28 b. 7
An analysis of variance comparing three treatment conditions produces dfwithin = 21.
An analysis of variance comparing three treatment conditions produces dfwithin = 21. If the samples are all the same size, how many individuals are in eachsample.a. 6b. 7c. 8d. It is impossible for the samples to be the same size if dfwithin = 21.
Which of the following plots can help determine whether the variance of the error terms is...
Which of the following plots can help determine whether the variance of the error terms is not constant? (Select all that apply) Select one or more: a. Scatter plot b. Absolute values of residuals or of squared residuals against fitted values. c. Residual plot against the fitted values d. Normal probability plot
25. An analysis of variance comparing 3 treatment conditions produces dfwithin 21. If the samples are...
25. An analysis of variance comparing 3 treatment conditions produces dfwithin 21. If the samples are all the same size, how many individuals are in each sample? a, 6 b. 7 c. 8 d. it is impossible for the samples to be the same size if dfwithin 21
Q3. 47 ptsSuppose the weight (y) of babies depends on their height (xi) and age (x2). The following table presents the data for a sample of 5 babies and some results of analysis of the data are...
Q3. 47 ptsSuppose the weight (y) of babies depends on their height (xi) and age (x2). The following table presents the data for a sample of 5 babies and some results of analysis of the data are also given below. 2 | 4 | 5 | 7|8| Given that (XX) xi | 1.5 | 2 | 2.5 | 3.5 | 3 | [16.4286-14.2857 4.428571 Corr matrix 1.00 0.985 0.985 1.000 0.8285 X2 1 35 7 614.2857 13.25714.285710.3142 3) 0.7142 4.42857-4.2857...
Question 5 1 pts Which of the following statements about multicollinearity are correct? Select all that are correct. If you cannot justify dropping an explanatory variable the best solution to multicollinearity may be to do nothing Multicollinearity is a much more serious problem than omitted variable bias Getting better data is a good solution to multicollinearity Perfect multicollinearity can be detected in Minitab by attempting to run a regression. If the data is perfectly collinear the regression will not run...
Question 33 What does regression analysis attempt to establish? o a. multicollinearity o b. linearity in the relationship between independent variables o c. a mathematical relationship between a dependent variable, for which future values will be forecast, and one or more independent variables with known values o d. linearity in the relationship between a dependent variable and a set of independent variables Question 34 How are states of nature assigned probabilities? oa. Use historical data. o b. Use best judgements....
4. The following is the output of linear regression analysis, which includes dummy variables and interactions. The following are the variables: Y = Birth weights of infants born in preterm in three hospitals (A, B and C) X = Gestation age in weeks flif infant was born in Hospital A 10 Otherwise s X2= flif infant was born in Hospital B 10 Otherwise Variable Coefficient Standard deviation 1 P (approximate) Constant -1.1361 4904 .07648 01523 .7433 .6388 X -.8239 .6298...
29. The following table shows the results of an analysis of variance comparing two treatment conditions with a sample of n = 11 participants in each treatment. Note th several values are missing in the table. What is the missing value for MSwithin? ss dfMS Source Between xx xx 14 F=xx Within Total 154 xx C. 14 d. 28 b. 7
25. An analysis of variance comparing 3 treatment conditions produces dfwithin 21. If the samples are all the same size, how many individuals are in each sample? a, 6 b. 7 c. 8 d. it is impossible for the samples to be the same size if dfwithin 21
Q3. 47 ptsSuppose the weight (y) of babies depends on their height (xi) and age (x2). The following table presents the data for a sample of 5 babies and some results of analysis of the data are also given below. 2 | 4 | 5 | 7|8| Given that (XX) xi | 1.5 | 2 | 2.5 | 3.5 | 3 | [16.4286-14.2857 4.428571 Corr matrix 1.00 0.985 0.985 1.000 0.8285 X2 1 35 7 614.2857 13.25714.285710.3142 3) 0.7142 4.42857-4.2857...
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