Okay, so when we consider a regression analysis, the slope of the graph (r) between the two variables (say X and Y) is actually defined as a ratio of the sum of products and the square root of the product of the sum of squares (of X) and the sum of squares (of Y). Thus, since the sum of squares is always positive, the Sum of Products determines whether the slope will be positive or negative.
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in regression analysis, the Sum of Products (SP) value will determine whether the slope will be...
Question 6A regression line can be used to determine the strength of a relationship. determine if there is a cause and effect relationship. predict Y for any X value. establish if a relationship is linear. Question 7 If the correlation coefficient R between two variables is ,it is expected that the slope of the regression line will be positive; positive positive; large negative; small positive; negative Question 8 If the slope of the simple regression line is .12, then the Pearson correlation coefficient r is expected to be positive negative small large
For the graph on the right, determine if the slope is positive, negative, or zero, and whether the y-value of the y-intercept is positive, negative, or zero. The slope is O A. negative. O B. zero. O C. positive. The y-value of the y-intercept is OA. negative. 10 10 B. zero. O C. positive.
Significance level of 0.05, test whether the slope of the regression line is negative. The regression equation is, Y = 6.0 - 0.7x predictor coef stdev t-ratio constant 6.0 2.558 2.32 X -0.7 0.086 -8.28 ANOVA source df ss ms F regression 1 648.12 648.12 68.58 error 6 56.72 9.45 total 7 704.84
Question 15 1 pts In a simple regression analysis (where y is a dependent and x an independent variable), if the y intercept is zero, then O the slope must be negative. o the slope can be positive, or zero, or negative. O there is no relationship between x and y. o the slope must be positive.
1. In regression analysis, the Sum of Squares Total (SST) is a. The total variation of the dependent variable b. The total variation of the independent variable c. The variation of the dependent variable that is explained by the regression line d. The variation of the dependent variable that is unexplained by the regression line Question 2 In regression analysis, the Sum of Squares Regression (SSR) is A. The total variation of the dependent variable B. The total variation of the independent variable...
If the coefficient of determination is a positive value, thenthe regression equation a) must have a positive slope b) must have a negative slope c) could have either a positive or negative slope d) must have a positive y intercept
State whether the following statements are correct or not in the context of regression analysis, and explain why: a. The sum of OLS residuals is zero. b. The OLS estimator of b0 of the regression equation y = b0 + u is the sample mean of y.
Significance level of 0.05, test whether the slope of the regression line is negative. Form a 95% confidence interval on the slope of the line. The regression equation is, Y = 6.0 - 0.7x predictor coef stdev t-ratio constant 6.0 2.558 2.32 X -0.7 0.086 -8.28 ANOVA source df ss ms F regression 1 648.12 648.12 68.58 error 6 56.72 9.45 total 7 704.84
8. Use the following information from a multiple regression analysis. n = 15 b1 = 5 b2 = 6 Sb1 = 1.4 Sb2 = 0.8 a. Which variable has the largest slope, in units of a t statistic? The variable _____ has the largest slope, with tSTAT = _____ b. Construct a 90% confidence interval estimate of the population slope, β1. c. Begin by determining whether X1 makes a significant contribution to the regression model. Determine the null and alternative...
For a simple linear regression results shown below, the P-value for the slope coefficient is as follows: a hypothesis test of whether the regression coefficient ß1 is zero. a measure that determines if the linearity assumption is satisfied a hypothesis test of whether the regression coefficient for Advertising is equal to 6.738. the variability of the observed Y-values from the predicted values.