The standard error of the estimate is
the amount of error that is calculated amongst variables |
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the same amount of error throughout, hence being standard |
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the measure of variability around the line of regression |
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the measure of the volatility of the independent variable |
Answer: Option ( 3), the measure of variability around the line of regression
The standard error of the estimate is the measure of variability around the line of regression
The standard error of the estimate is the amount of error that is calculated amongst variables...
Simple Linear Regression Problem 3 points Save Answer QUESTION 1 The standard error of the estimate is the amount of error that is calculated amongst variables the same amount of error throughout, hence being standard the measure of variability around the line of regression the measure of the volatility of the independent variable 2 pointsSave Answer QUESTION 2 The Maroochy Chamber of Commerce is interested in determining the relationship between the number of fine days each year and the number...
With regard to a regression-based forecast, the standard error of the estimate gives a measure of: A. the time required to derive the forecast equation. B. the maximum error of the forecast. C. the variability around the regression line. D. the time period for which the forecast is valid.
Error in prediction (error of estimate) is calculated as the distance between each individual data point and the regression line. A) True B) False
The scatterplot, created from 1995 U.S. News & World Report data on approximately 1,300 U.S. colleges and universities, depicts the relation between the student-faculty ratio at the school and the number of admissions applications the school received. Figure: Student-Faculty Ratio 50.000 40.000 30.000 Applications received 20.000 10.000 0 100 0 20 40 60 BO Student-faculty ratio 18. (Figure: Student-Faculty Ratio) Based on the scatterplot, what is the relation between an institution's student-faculty ratio and the number of applications it receives?...
D Question 7 2 pts Only coefficients with a large standard error can be statistically significant. True False D Question 8 1 pts If you estimate a regression model and the R-square is 0.50, how much of the variation in the dependent variable is explained by the independent variables O 10% O 25% 50% О 100%
12. The______ measures the reliability of the estimation equation. a. standard deviation b. Standard error of the estimate c. Type 1 error d. Type 11 error 13. The________ is similar to the standard deviation in that both are measures of variability. a. variance b. standard error of the estimate c. type 1 error d. type 11 error 15. The __________ is used to describe the correlation between two variables. a. coefficient of determination b. correlation coefficient c. intelligence coefficient d....
5) In a regression model developed to estimate cruise vacation prices, two recorded independent variables were: ship Size (sqft) and ship Capacity (number of people). A correlation analysis yielded the following table: Size Capacity Size Capacity 0.88091 a. There is a high positive correlation between ship Size and ship Capacity. b. Each variable is perfectly correlated with itself. c. One of these two variables should be excluded from the regression model to avoid multicollinearity. d. All of the above statements...
18. Regarding the standard error of the estimate (SEE or Sy/x)-more than one answer may be correct a. The SEE describes the dispersion of x, y points around the regression line b. If the random errors for both methods are identical, the SEE will be approximately 1.4 times a typical SD c. The SEE is used to evaluate the accuracy of a method based on hemolysis and lipemia interference experiments The SEE is sensitive to random error d. 18. Regarding...
If alpha is set to .05, what will the level of Type II error be? 0.05 0.95 0 Cannot say Heteroscedasticity occurs when: there are larger values on X than Y. there is a linear relationship between X and Y. more error is accounted for than remains. variability in Y depends on the exact value of X. The variables that are measured throughout the experiment are called: Control Dependent variable Independent variable Responding variable
:2. A study was conducted in which participants looked at photographs of various people and guessed how old each photographed person was. Then the amount of error in each guess was calculated, and this was used as a response variable in regression analyses. Here are the names of the variables used; these will be referenced in the questions below: Error: Difference between guessed age and true age. (Positive errors are overestimates, i.e. guessing an age greater than true age; negative...