The equation of a certain linear regression line is ˆy = 0.93x + 20.84. For x = 18, y is observed to be 38. What is the residual?
(a) -1.42
(b) -0.42
(c) 0
(d) 0.42
(e) 1.42
The equation of a certain linear regression line is ˆy = 0.93x + 20.84. For x...
Using simple linear regression analysis, the equation for a line through the data is estimated to be y = 1.9 + 0.55. For each of the x values, calculate the observed y. the predicted y and the residual. 4.3 For the following four regression equations, explain what the slope and intercept mean. a. wage = 2.05 + 1.32education, where wages dollars earned per hour and educa- b. GPA c, sleep 10.33-0.44work, where sleep is hours spent sleeping per night and...
QUESTION 1In a simple linear regression model, the intercept of the regression line measuresa.the change in Y per unit change in X.b.the change in X per unit change in Y.c.the expected change in Y per unit change in X.d.the expected change in X per unit change in Y.e.the value of Y when X equals 0.f.the value of X when Y equals 0.g.the average value of Y when X equals 0.h.the average value of X when Y equals 0.QUESTION 2In a...
In the simple linear regression equation, (y a+ bx+ e), the a is the... O A. independent variable O B. slope of the fitted line C. dependent variable O D.y-intercept Reset Selection Question 2 of 5 1.0 Points In the simple linear regression equation, (y a+bx+ e) the y is the O A. independent variable O B. dependent variable O C. slope of the fitted line D. y-intercept Question 3 of 5 1.0 Points The R2 for a regression model...
A researcher used a linear regression model to investigate the relationship betweensexually transmitted disease rate (y) and poverty rate (x) in the U.S.A. The scatterplotof y-variable verses the x-variable was approximately linear.The regression function is: ˆy= 105.09 + 29.3xFor a state in this study, the poverty rate is 14.5, and sexually transmitted diseaserate is 495.2. What is the residual for this observation?
Q5). Show that in a simple linear regression Σεί 0 (a). (). (X,Y) is a point on the fitted regression line. (d). Verify parts (a), (b), and (c) for the data in the folder "Regression and Correlation" at the course blackboard site. You are free to use software or calculator for the verification. Q5). Show that in a simple linear regression Σεί 0 (a). (). (X,Y) is a point on the fitted regression line. (d). Verify parts (a), (b), and...
find a linear (regression) equation with following data. Answer y= ( ) + ( )* x (X, Y) (30, 12) (40, 20) (50, 24) (60, 38) (70, 40)
A linear regression equation has a slope b = 3 and a constant a = 4 . What is the predicted value of Y for X = 10? inear regression equation has a slope b = 3 and a constant a = 4 . What is the predicted value of Y for X = 10? A. 12.0 B. 20 C. 28 D. 34 E. 36 F. None of the above.
519 Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful The table below shows the heights (in feet) and the number of stories of six notable buildings in a city Height, 778 621 510 494 473 (a) x...
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city Height, x 768 628 518 511 491 478 (a)...
Select all of the following statements that are true about linear regression analysis of quantitative variables. If the purpose of our regression model is prediction, it does not matter which variables we define as the explanatory and response variable. The observed values of Y will fall on the estimated regression line, while the predicted values of Y will vary around the regression line. The purpose of linear regression is to investigate if there exists a linear relationship between a response...