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
Homework Answers
The plots that can help us in figuring out whether the variance of the error terms is not constant are:
Absolute values of residuals or of squared residuals against fitted values.
Residual plot against the fitted values
Option B and Option C are correct.
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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 a linear regression function is appropriate for...
Which of the following plots can help determine whether a linear regression function is appropriate for the data being analyzed? (Select all that apply) Select one or more: a. Scatter plot b. Residual plot against the predictor variable c. Residual plot against the fitted values d. Normal probability plot
If a diagnostic plot shows residuals (i.e., error terms) get wider as the value of the...
If a diagnostic plot shows residuals (i.e., error terms) get wider as the value of the predicted value (x) increases (i.e., an “open megaphone” shape), then this is indicative of a violation of which linear regression assumption? Select one: a. No outliers b. Analysis of variance c. Constant variance
(4 points) Residuals vs fitted plots can be used to assess whether the four key assumptions for a...
(4 points) Residuals vs fitted plots can be used to assess whether the four key assumptions for a simple linear regression have been met. Each of the plots below displays an instance where at least one of these assumptions may not have been met. For each plot, identify which assumption has been most violated, if any. 1. Plot A shows that A. The relationship between x and y cannot be assumed to be linear. B. The residuals do not appear...
ONLY NEES A,B help please!!! 1II. (10 pts) You are given the following estimated equation In(wage)- 0.3688+0.0852educ + 0.05 teure-0.000994tenue 0.0908) (0.0069) (0.0068) (0.00025) R-0.3294 526...
ONLY NEES A,B help please!!!
1II. (10 pts) You are given the following estimated equation In(wage)- 0.3688+0.0852educ + 0.05 teure-0.000994tenue 0.0908) (0.0069) (0.0068) (0.00025) R-0.3294 526 in which: logtwage) log of average hourly wage; educ is the number of years of schooling tenure is the number of years of tenure fenure tenure remure The plot of the residuals against the fitted values from the regression above, is provided below: 2.5 1.5 Fitted values .5 a. With a 1% significance level,...
Which of the following are assumptions for the linear regression model? CHECK THAT ALL MAY APPLY!!! Select one or more: a. Regression function (i.e., equation) is linear. b. Error terms are normall...
Which of the following are assumptions for the linear regression model? CHECK THAT ALL MAY APPLY!!! Select one or more: a. Regression function (i.e., equation) is linear. b. Error terms are normally distributed. c. Error terms are independent. d. Error terms have constant variance. e. Regression model fits all observations (i.e., no outliers).
5.) You can NOT use a regression for which of the following activities? a.) You can...
5.) You can NOT use a regression for which of the following activities? a.) You can in fact use a regression model for all of these b.) Forecasting new observations c.) Identifying unusual data points d.) Measuring the proportion of variability in the outcome variable explained by the predictor variables 6.) A simple regression equation decomposes the observed data into two parts: the fitted values and the residuals. What is the interpretation of a residual? a.) The horizontal distance from...
Hi, Could someone please give detail explanation of the following graphs. I try to understand wha...
Hi,
Could someone please give detail explanation of the following
graphs. I try to understand what assumptions are being violate here
ie (constant variance, independent residuals, linearity) sample
size is n=270 observation. I think the variance in top left graph
is not constant; there is huge gap in middle of data, but i do not
know how to explain formally,
I really looking for someone who has a strong understanding of
statistics to provide justification. I want to understand if...
A random sample of 214 junior and senior college students was taken. Each student reported the...
A random sample of 214 junior and senior college students was
taken. Each student reported the average amount of sleep they get
per night (in minutes) and their current college GPA. Plots from a
simple linear regression analysis are displayed below.
Which of the following is true about the linearity
condition?
1.The linearity condition is not satisfied because there is
curvature in the normal probability plot of the residuals.
2.The linearity condition is satisfied because most of the
residuals...
An article in the ACI Materials Journal (Vol. 84, 1987, pp. 213-216) describes several experiments investigating...
An article in the ACI Materials Journal (Vol. 84, 1987, pp. 213-216) describes several experiments investigating the rodding of concrete to remove trapped air. A 3-inch x 6-inch cylinder was used, and the number of times this rod was used is the design variable. The resulting compressive strength of the concrete specimen is the response. The data are shown in the following table. Compressive Strength (psi) Rodding Level Observations 10 1530 1530 1440 15 1610 1650 1500 20 1560 1730...
QUESTION 19 For the following software output, check each assumption/condition to run linear regression and state...
QUESTION 19 For the following software output, check each assumption/condition to run linear regression and state whether it is appropriate to use linear regression. Bivariate Fit of pluto By alpha 20 15 10 5 0 e 0.05 0.15 C 0.1 alpha Linear Fit Linear Fit pluto -0.597417 16543195*alpha Summary of Fit RSquare RSquare Adj Root Mean Square Error Mean of Response Observations (or Sum Wgts) 0.915999 0.911999 2.172963 6.73913 23 Analysis of Variance Sum of DF Squares Mean Square Source...
ONLY NEES A,B help please!!!
1II. (10 pts) You are given the following estimated equation In(wage)- 0.3688+0.0852educ + 0.05 teure-0.000994tenue 0.0908) (0.0069) (0.0068) (0.00025) R-0.3294 526 in which: logtwage) log of average hourly wage; educ is the number of years of schooling tenure is the number of years of tenure fenure tenure remure The plot of the residuals against the fitted values from the regression above, is provided below: 2.5 1.5 Fitted values .5 a. With a 1% significance level,...
Hi,
Could someone please give detail explanation of the following
graphs. I try to understand what assumptions are being violate here
ie (constant variance, independent residuals, linearity) sample
size is n=270 observation. I think the variance in top left graph
is not constant; there is huge gap in middle of data, but i do not
know how to explain formally,
I really looking for someone who has a strong understanding of
statistics to provide justification. I want to understand if...
A random sample of 214 junior and senior college students was
taken. Each student reported the average amount of sleep they get
per night (in minutes) and their current college GPA. Plots from a
simple linear regression analysis are displayed below.
Which of the following is true about the linearity
condition?
1.The linearity condition is not satisfied because there is
curvature in the normal probability plot of the residuals.
2.The linearity condition is satisfied because most of the
residuals...
An article in the ACI Materials Journal (Vol. 84, 1987, pp. 213-216) describes several experiments investigating the rodding of concrete to remove trapped air. A 3-inch x 6-inch cylinder was used, and the number of times this rod was used is the design variable. The resulting compressive strength of the concrete specimen is the response. The data are shown in the following table. Compressive Strength (psi) Rodding Level Observations 10 1530 1530 1440 15 1610 1650 1500 20 1560 1730...
QUESTION 19 For the following software output, check each assumption/condition to run linear regression and state whether it is appropriate to use linear regression. Bivariate Fit of pluto By alpha 20 15 10 5 0 e 0.05 0.15 C 0.1 alpha Linear Fit Linear Fit pluto -0.597417 16543195*alpha Summary of Fit RSquare RSquare Adj Root Mean Square Error Mean of Response Observations (or Sum Wgts) 0.915999 0.911999 2.172963 6.73913 23 Analysis of Variance Sum of DF Squares Mean Square Source...
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