Some X, Y data are positively correlated with r = 0.5. Also:
| x̄ = 4 | Sx = 2 |
| ȳ = 6 | Sy = 3 |
a. Find the equation for the regression line
b. Predict Y for X = 8
c. Find the coefficient of determination and interpret its meaning.

Some X, Y data are positively correlated with r = 0.5. Also: x̄ = 4 Sx...
Some X, Y data are positively correlated with r = .70. Also: bar x = 10 bar y = 7 sx = 2 sy = 4 a. Find the equation for the regression line. b. Predict Y if X = 9 c. Find the coefficient of determination.
Given that x = 3.5000, sx = 2.5884, y = 4.1000, sy = 1.9657, and r
= -0.9552, determine the least-squares regression line.
y = ____ x + (_____)
A data set is given below. (a) Draw a scatter diagram. Comment on the type of relation that appears to exist be (b) Given that x = 3.5000, Sy = 2.5884, y = 4.1000, sy = 1.9657, and r = -0.9552, det (c) Graph the least squares regression line on the...
we have a bivariate data set and compute the following: r=.7, sy=9, sx=5, x-bar=13.5, y=51.6. We want to know the equation of the least-squares regression line, but we don't have a calculator. Determine the equation of the least-squares regression line from the given data. a. y=46.34+.39x b. y=-51.52+1.26x c. y=34.59+1.26x d. y=-6.624+.39x e. you can't compute the regression line without knowing the original data.
Given a correlation coefficient (r) of 0.7216, mean of x-bar = 140.5, standard deviation of x (sx) = 6.4, mean of y-bar = 128.3, and standard deviation of y (sy) = 8.2. Find the slope of the regression line. Find the y-intercept of the line. Write the equation of the line.
Part of an Excel output relating 15 observations of X (independent variable) and Y (dependent variable) is shown below. Provide the values for a-e shown in the table below. (See section 15.5) Summary Output ANOVA df SS MS F Significance F Regression 1 2.7500 -d- -e- 0.632 Residual -a- -b- 11.45 Total 14 -c- A Company has recorded data on daily demand for its product (y in thousands of units) and the unit price (x in hundreds of dollars). A...
An alternate expression for the slope coefficient of the simple linear regression model is B1= r(Sy/Sx) where r is the Pearson correlation coefficient given by r= Sxy/ (√(SxxSyy) and Sy and Sx are the sample standard deviations of y and x, respectively. Use the data to show that this alternate formulation gives a slope coefficient that is numerically equivalent to what you found using the Least-squares estimations demonstrating that r(Sy/Sx) = Sxy/Sxx. Using the information given, find B0 and B1...
4. The data set below shows the length of service (in years)and salaries in thousands of dollars) for 10 randomly selected employees. Length of service, 2 Salary, y 0.5 2 4 6 8 10 .75 39 41 41 40.5 42 41 40 1 6 8 38 41 42 (a) Construct a scatter plot for the data showing the regression line. (b) Find the equation of the regression line for the data. (c) Find the value of the correlation coefficient, r....
Suppose that you are given the following results. Find the correlation coefficient of the data. sx = 2.391, sy = 13.200, b = -4.780 a) 0.155 b) -0.866 c) -0.433 d) -0.155 e) 0.866 f) None of the above Suppose you find that the correlation coefficient for a set of data is 0.841. What is the coefficient of determination and what does it mean? a) 0.841; This means that 84.1% of the variation of y is explained by the LSRL...
In a simple linear regression study between two variables x ( the independent variable) and y (the dependent variable), a random large sample is collected and the coefficient of correlation r = −.98 is calculated. A)Which of the following conclusion may be made? Group of answer choices x and y are almost perfectly correlated, and y increases as x is increased. x and y are almost perfectly correlated, and y decreases as x is increased. x and y are moderately...
The data below represent commute times (in minutes) and scores on a well-being survey. Commute Time (minutes), x 5 20 25 40 50 84 105 Well-Being Index Score, y 69.2 68.0 67.4 66.6 66.2 65.1 63.3 Given that r = -0.9841, Sx = 35.981, Sy = 1.942. a) Find the equation for the regression line. b) Interpret the slope and y-intercept. c) Find the predicted value of index score when x = 40. Find the residual for the value of...