Question

An animal trainer tests whether the number of hours of obedience training can predict where a dog places in a dog show. The hypothetical data are given below. Hours of Training Place in Breed Show Y 21 4 13 2 10 In terms of the method of least squares, which of the following regression lines is the best fit for these data? O Ÿ = -0.338x + 7.559 O Ÿ = 0.338X - 7.559 O Ÿ = -1.2x - 4.75 o Û = 1.2x + 4.75 Additional Materials

Answer 1

We can use here Excel for regression equation

Step 1) Enter data in Excel .

Step 2) Data >>Data analysis >>Regression >>Select y and x values separately >>Ok

$\hat{Y}=-0.338x+7.559$

fx Intercept A B C H к L M N P SUMMARY OUTPUT mt n Regression Statistics Multiple R 0.917585835 R Square 0.841963764 Adjusted RSC 0.762945646 Standard Errc 1.079591238 Observations Chart Title ANOVA o Regression Residual Total SS MS 1 12.41897 12.4189 2 2.331034 1.1655: 3 14.75 Axis Title Series1 Linear (Series1) Y Coefficients andard Errt Stat 7.55862069 1.426053 5.30031 -0.337931034 0.103525 -3.264 TO -0.337x + 7.558 R?=0.842 Intercept X Variable 1 JT 5 10 15 20 25 ga Axis Title