If the p-value of F tests in the Excel linear regression outputis 0.7, then there is no statistical evidence to suggest that:O a. all individual regression coefficients are zero.O b. one or more independent variables are associatedwith the dependent variable.O c. all individual regression coefficients are zero; one ormore independent variables are associated with thedependent variable.O d. one or more regression coefficients are zero.O e.one or more regression coefficients are notzero; one or more independent variables areassociated with the dependent variable.

The p-value of F tests in the Excel linear regression output is 0.7.

Answered: If the p-value of F tests in the Excel…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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2. Consider the foot length and foot width of six female grade 4 students in Morning Star Montessori School in 2006: Length of foot (cm) Y 20.9 Width of foot (cm) X 8.5 24 9 19.6 7.9 22.6 8.8 21 8.8 21.6 9.3 c) What is the least squares regression line for Y as a function of X?
A vocational counselor uses the number of days without employment to predict her clients' feelings of self efficacy, measured on a scale of 1 to 5, with higher numbers meaning that clients feel more secure in their job related abilities. The slope of the regression line is –1.02. Which statement is the best interpretation for this finding? a. For every 1-point increase in self-efficacy, there is an associated decrease in the number of days of unemployment. b. For every additional day of unemployment, there is an associated decrease in self-efficacy of 1.02 points. c. The least number of days a person can be unemployed and still feel self-efficacious is 3.98 points d. The decrease in self-efficacy of 1.02 points is caused by each additional day of unemployment
If all the points of a scatter diagram lie on the least squares regression line, then the coefficient of determination for these variables based on these data _____. Select one: A. is 0 B. could be any value between -1 and 1 C. is either 1 or -1, depending upon whether the relationship is positive or negative D. is 1
Which of the following is(are) TRUE if the coefficient of determination between the response and the predictor variables is 0.81 based on a random sample of size n. O Neither Anor B O A. This means that 19% of the total variation in the response variable remains unexplained by the simple linear regression model that uses the given predictor variable. O Both A and B B. The Pearson's sample correlation coefficient is +0.9.
Suppose x1 ans x2 are predictor variables for a response variable y. a. The distribution of all possible values of the response variable corresponding to particular values of the two predictor variables is called a distribution of the response variable. b. State the four assumptions for multiple linear regression inferences.
Body Fat. Where we considered the regression of percentage of body fat on nine body measurements: height, weight, hip, forearm, neck, wrist, triceps, scapula, and sup. Use the technology of your choice to do the following. a. Use the maximum- R2 criterion to obtain a regression equation for these data. b. Use the adjusted- R2 criterion to obtain a regression equation for these data. c. Use the Mallows’ Cp criterion to obtain a regression equation for these data. d. Are the regression equations obtained in parts (a), (b), and (c) the same? e. Use the analysis in parts (a), (b), and (c) to select a regression equation for these data. For the regression equation that you selected, obtain plots of residuals versus fitted values, residuals versus the included predictor variables, and a normal probability plot of the residuals. Perform a residual analysis to assess the appropriateness of the regression equation, constancy of the conditional standard deviations, and normality of the…
. Interpret your result from part (a) if the assumptions for regression inferences hold. Choose the correct interpretation below. A. Presuming that the variables age and price for Corvettes satisfy the assumptions for regression inferences, the standard error of the estimate provides an estimate for the common population standard deviation, σ, of ages for all Corvettes of any particular price. B. Presuming that the variables age and price for Corvettes satisfy the assumptions for regression inferences, the standard error of the estimate provides an estimate for the slope, β1, of the population regression equation for ages for all Corvettes of any particular price. C. Presuming that the variables age and price for Corvettes satisfy the assumptions for regression inferences, the standard error of the estimate provides an estimate for the common population standard deviation, σ, of prices for all Corvettes of any particular age. D. Presuming that…
12. measures the strength of the relationship between the dependent and independent variables. 13. One way to examine whether two variables might be linearly related is to construct a 14. The assumption of equal standard deviations about the regression line is called
Select all statements that are true of the least-squares regression line. ) It assumes a linear relationship between the explanatory and the response variable. R-squared is the portion of sample variance in the explanatory variable that can be explained by variation in the response variable. ) It can be used to predict the mean response of the explanatory variable. | R-squared is the portion of sample variance in the y variable that can be explained by variation in the x variable.
12. Which of the following statistic in the Multiple Regression Analysis SPSS output shows the magnitude and direction of the overall correlation of variables, meaning the magnitude and direction of the correlation of all predictor variables (X1, X2, X3,...Xn) with the criterion variable (Y)? * O F O R O Beta
Suppose that x and y are two variables of a population and that the assumptions for regression inferences are met with x as the predictor variable and y as the response variable. a. What statistic is used to estimate the slope of the population regression line? b. What statistic is used to estimate the y-intercept of the population regression line? c. What statistic is used to estimate the common conditional standard deviation of the response variable corresponding to fixed values of the predictor variable?

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