A regression equation estimating left palm length (Y variable) based on right palm length (X variable)...
A regression equation estimating left palm length (Y variable) based on right palm length (X variable) based on a sample of 55 college students resulted in an error sum of squares (SSE) of 10.7 and a total sum of squares (SST) of 85.2. The R2 for this model is ______.
a. 87.4%
b. 12.6%
c. 74.5%
d. Cannot be determined from the information provided
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A regression equation estimating left palm length (Y variable)
based on right palm length (X variable)...
A representative sample of 190 students resulted in a regression equation between y = left hand...
A representative sample of 190 students resulted in a regression equation between y = left hand spans (cm) and x = right hand spans (cm). The least squares regression equation is û = 1.46 +0.938.x. The error sum of squares (SSE) was 76.67, and total sum of squares (SST) was 784.8. What is the value of p2, the proportion of variation in left hand spans explained by the linear relationship with right hand spans? Select one: a. None of the...
7,10,11 Based on the following regression output, what is the equation of the regression line? Regression...
7,10,11
Based on the following regression output, what is the equation of the regression line? Regression Statistics Multiple R 0.917214 R Square 0.841282 Adjusted R Square 0.821442 Standard Error 9.385572 Observations 10 ANOVA df SS MS Significance F 1 Regression 3735.3060 3735.30600 42.40379 0.000186 8 Residual 704.7117 88.08896 9 Total 4440.0170 Coefficients Standard Error t Stat P-value Lower 95% Intercept 31.623780 10.442970 3.028236 0.016353 7.542233 X Variable 1.131661 0.173786 6.511819 0.000186 0.730910 o a. 9; = 7.542233+0.7309 Xli o b....
The data shown below for the dependent variable, y, and the independent variable, x, have been...
The data shown below for the dependent variable, y, and the independent variable, x, have been collected using simple random sampling. X 10 15 11 19 18 17 5 17 18 y 9070 30 8020 30 5060 40 40 a. Develop a simple linear regression equation for these data. b. Calculate the sum of squared residuals, the total sum of squares, and the coefficient of determination c. Calculate the standard error of the estimate. d. Calculate the standard error for...
Consider a multiple regression model of the dependent variable y on independent variables x1, X2, X3, and x4: Using data with n 60 observations for each of the variables, a student obtains the follow...
Consider a multiple regression model of the dependent variable y on independent variables x1, X2, X3, and x4: Using data with n 60 observations for each of the variables, a student obtains the following estimated regression equation for the model given: y0.35 0.58x1 + 0.45x2-0.25x3 - 0.10x4 He would like to conduct significance tests for a multiple regression relationship. He uses the F test to determine whether a significant relationship exists between the dependent variable and He uses the t...
33. Based on the regression In Y, =a+ß, In X, , where Y is the quantity...
33. Based on the regression In Y, =a+ß, In X, , where Y is the quantity of beef and X is beef price, and "In" stands for natural logarithm, we obtain the following regression output based on 100 observations: Dependent Variable: In Y Variable Intercept In X Parameter Estimate (a) ? -0.20 Standard Error t-value 2.175 1.300 0.0341 -5.865 r?: 0.258 What are the degrees of freedom in this model? a. 100. b. 2. c. 99. d. 98. e. Cannot...
4. Testing for significance Aa Aa Consider a multiple regression model of the dependent variable y on independent variables x1, x2, X3, and x4: Using data with n = 60 observations for each of the var...
4. Testing for significance Aa Aa Consider a multiple regression model of the dependent variable y on independent variables x1, x2, X3, and x4: Using data with n = 60 observations for each of the variables, a student obtains the following estimated regression equation for the model given: 0.04 + 0.28X1 + 0.84X2-0.06x3 + 0.14x4 y She would like to conduct significance tests for a multiple regression relationship. She uses the F test to determine whether a significant relationship exists...
Name Economics 5 Ch 13 Practice The follo wing data are the monthly salaries y and the grade point averages x for students who obtained a bachelor's degree in business administ ration Obser vatio...
Name Economics 5 Ch 13 Practice The follo wing data are the monthly salaries y and the grade point averages x for students who obtained a bachelor's degree in business administ ration Obser vation index xi 2.6 3300 3.4 3600 3.6 4000 3.2 3500 3.5 3900 2.9 3600 TSS Totals SSR SSE 1. Calculate and y 2. Use the least squares method to develop the estimated regression equation. Use two decimal points in your answers for bo and bi. 3....
6. Interpreting statistical software output in regression Aa Aa Suppose you work in the admission...
6. Interpreting statistical software output in regression Aa Aa Suppose you work in the admissions department of a small liberal arts college. You wonder if you can predict students' college grade point averages (GPAs) by their SAT scores. You randomly select 50 recent graduates and collect their SAT scores and college GPAs. You use a statistical software package to run a regression predicting college GPA from SAT score. Use the following output to answer the questions that follovw Descriptive Statistics...
r studio answer to these questions What is the intercept parameter (2dp) for the regression equation of height (y) versus age (x) using the pine_growth.csv data? What is the total amount of variation...
r studio answer to these questions What is the intercept parameter (2dp) for the regression equation of height (y) versus age (x) using the pine_growth.csv data? What is the total amount of variation explained by the regression model (SSr) of height (y) versus age (x) using the pine_growth.csv data? What is the residual error sum of squares (SSe) of a regression model of height (y) versus age (x) using the pine_growth.csv data. Use your regression equation fitted to the pine_growth.csv...
Values of modulus of elasticity (MOE, the ratio of stress, i.e., force per unit area, to...
Values of modulus of elasticity
(MOE, the ratio of stress, i.e., force per unit area, to strain,
i.e., deformation per unit length, in GPa) and flexural strength (a
measure of the ability to resist failure in bending, in MPa) were
determined for a sample of concrete beams of a certain type,
resulting in the following data (read from a graph in the article
"Effects of Aggregates and Microfillers on the Flexural Properties
of Concrete"†).
Concrete"T). MOE 29.8 33.2 33.7 35.3...
A representative sample of 190 students resulted in a regression equation between y = left hand spans (cm) and x = right hand spans (cm). The least squares regression equation is û = 1.46 +0.938.x. The error sum of squares (SSE) was 76.67, and total sum of squares (SST) was 784.8. What is the value of p2, the proportion of variation in left hand spans explained by the linear relationship with right hand spans? Select one: a. None of the...
7,10,11
Based on the following regression output, what is the equation of the regression line? Regression Statistics Multiple R 0.917214 R Square 0.841282 Adjusted R Square 0.821442 Standard Error 9.385572 Observations 10 ANOVA df SS MS Significance F 1 Regression 3735.3060 3735.30600 42.40379 0.000186 8 Residual 704.7117 88.08896 9 Total 4440.0170 Coefficients Standard Error t Stat P-value Lower 95% Intercept 31.623780 10.442970 3.028236 0.016353 7.542233 X Variable 1.131661 0.173786 6.511819 0.000186 0.730910 o a. 9; = 7.542233+0.7309 Xli o b....
The data shown below for the dependent variable, y, and the independent variable, x, have been collected using simple random sampling. X 10 15 11 19 18 17 5 17 18 y 9070 30 8020 30 5060 40 40 a. Develop a simple linear regression equation for these data. b. Calculate the sum of squared residuals, the total sum of squares, and the coefficient of determination c. Calculate the standard error of the estimate. d. Calculate the standard error for...
Consider a multiple regression model of the dependent variable y on independent variables x1, X2, X3, and x4: Using data with n 60 observations for each of the variables, a student obtains the following estimated regression equation for the model given: y0.35 0.58x1 + 0.45x2-0.25x3 - 0.10x4 He would like to conduct significance tests for a multiple regression relationship. He uses the F test to determine whether a significant relationship exists between the dependent variable and He uses the t...
33. Based on the regression In Y, =a+ß, In X, , where Y is the quantity of beef and X is beef price, and "In" stands for natural logarithm, we obtain the following regression output based on 100 observations: Dependent Variable: In Y Variable Intercept In X Parameter Estimate (a) ? -0.20 Standard Error t-value 2.175 1.300 0.0341 -5.865 r?: 0.258 What are the degrees of freedom in this model? a. 100. b. 2. c. 99. d. 98. e. Cannot...
4. Testing for significance Aa Aa Consider a multiple regression model of the dependent variable y on independent variables x1, x2, X3, and x4: Using data with n = 60 observations for each of the variables, a student obtains the following estimated regression equation for the model given: 0.04 + 0.28X1 + 0.84X2-0.06x3 + 0.14x4 y She would like to conduct significance tests for a multiple regression relationship. She uses the F test to determine whether a significant relationship exists...
Name Economics 5 Ch 13 Practice The follo wing data are the monthly salaries y and the grade point averages x for students who obtained a bachelor's degree in business administ ration Obser vation index xi 2.6 3300 3.4 3600 3.6 4000 3.2 3500 3.5 3900 2.9 3600 TSS Totals SSR SSE 1. Calculate and y 2. Use the least squares method to develop the estimated regression equation. Use two decimal points in your answers for bo and bi. 3....
6. Interpreting statistical software output in regression Aa Aa Suppose you work in the admissions department of a small liberal arts college. You wonder if you can predict students' college grade point averages (GPAs) by their SAT scores. You randomly select 50 recent graduates and collect their SAT scores and college GPAs. You use a statistical software package to run a regression predicting college GPA from SAT score. Use the following output to answer the questions that follovw Descriptive Statistics...
Values of modulus of elasticity
(MOE, the ratio of stress, i.e., force per unit area, to strain,
i.e., deformation per unit length, in GPa) and flexural strength (a
measure of the ability to resist failure in bending, in MPa) were
determined for a sample of concrete beams of a certain type,
resulting in the following data (read from a graph in the article
"Effects of Aggregates and Microfillers on the Flexural Properties
of Concrete"†).
Concrete"T). MOE 29.8 33.2 33.7 35.3...
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