Question

Suppose a teacher recorded the attendance of her students in a recent statistics class because she wanted to investigate the linear relationship between the number of classes they missed and their final grades. The accompanying table shows these data for a random sample of nine students

Classes Missed Final Grade
4   73
6   81
1   92
4   72
0   94
2   86
0   89
5   87
2   96 Suppose a teacher recorded the attendance of her students in a recent statistics class because she wanted to investigate the

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Answer #1

a) The correlation coefficient is given by

r={n\sum xy -(\sum x)(\sum y)\over \sqrt{[n\sum x^2-(\sum x)^2][n\sum y^2-(\sum y)^2]}}

Take x as represents number of missed classes and y denotes final grades

using the data given we get

r\approx -0.639

b) The null and the alternative hypothesis are

H_0: \rho =0 \\~~~~~~ H_a: \rho<0

The value of the test static is t={r\sqrt{n-2}\over \sqrt{1-r^2}}={-0.639\sqrt{9-2}\over \sqrt{1-(-0.639)^2}}\approx -2.20

The test is left tailed test, number of degrees freedom is 9-2=7

So P-value P(t<-2.20)=0.032

Since 0.032<0.05, we reject the null hypothesis.

There is sufficient evidence to support the claim that correlation coefficient is less than zero

c) There is negative correlation between the two

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