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Return to the data on maximum lean angle given in Exercise 28 of this chapter. Carry out a test at significance level .10 to see whether the population standard deviations for the two age groups are different (normal probability plots support the necessary normality assumption).

Short Answer

Expert verified

Do not reject null hypothesis and there is no statistical significant difference between the two standard deviations.

Step by step solution

01

To Find the hypothesis

Testing null hypothesis \({H_0}:\sigma _1^2 = \sigma _2^2\) versus alternative hypothesis\({H_a}\), under the assumption that the two populations are normal and independent, can be performed using test statistic value

\(f = \frac{{s_1^2}}{{s_2^2}}\)

Depending on alternative hypothesis \({H_a}\) the \(P\)value is corresponding area under the \({F_{m - 1,n - 1}}\)curve.

The hypotheses of interest are \({H_0}:\sigma _1^2 = \sigma _2^2\)versus\({H_a}:\sigma _1^2 \ne \sigma _2^2\). The missing values to compute the \(f\) value are the sample standard deviations \({s_1}\)and \[{s_2}\]

The Sample Variance \[{s_2}\] is

\({s^2} = \frac{1}{{n - 1}} \cdot {S_{xx}}\)

where

\({S_{xx}} = \sum {{{\left( {{x_i} - \bar x} \right)}^2}} = \sum {x_i^2} - \frac{1}{n} \cdot {\left( {\sum {{x_i}} } \right)^2}\)

The Sample Standard Deviation\(s\)is

\(s = \sqrt {{s^2}} = \sqrt {\frac{1}{{n - 1}} \cdot {S_{xx}}} \)

Thus, since\(m = 10\)and\[n = 5,\]the sample standard deviations are

\({s_1}{\rm{ }} = \sqrt {\frac{1}{{10 - 1}} \cdot \left[ {\left( {{{29}^2} + {{34}^2} + \ldots + {{27}^2}} \right) - \frac{1}{{10}} \cdot {{(29 + 34 + \ldots + 27)}^2}} \right]} \)

\( = 2.75\)

and

\({s_1}{\rm{ }} = \sqrt {\frac{1}{{5 - 1}} \cdot \left[ {\left( {{{18}^2} + {{15}^2} + \ldots + {{12}^2}} \right) - \frac{1}{5} \cdot {{(18 + 15 + \ldots + 12)}^2}} \right]} \)

\( = 4.44\)

02

Computing the test statistic

Therefore, the\(f\)statistic value is

\(\begin{array}{c}f = \frac{{{{2.75}^2}}}{{{{4.44}^2}}}\\ = 0.384\end{array}\)

03

Finding P-value

The corresponding \(P\)value, because the alternative hypothesis is two sided, is

\(2 \cdot {\rm{min}}\left( {{A_R},{A_L}} \right)\)

Using software, it is easy to obtain the values to the left of\(f\)value

\({A_L} = P(F \le 0.384) = 0.107.\)

and to the right of\(f\)

\({A_R} = P(F > 0.384) = 0.893\)

Where\(f\)has Fisher's distribution with\(m - 1 = 10 - 1 = 9\)and\(n - 1 = 5 - 1 = 4\)degrees of freedom. The minimum value is\[{A_L},\]thus the\(P\)value is

\(\begin{array}{c}P = 2{A_L}\\ = 2 \times 0.107\\ = 0.214\end{array}\)

04

Decision rule and conclusion

The \(P\) value could be obtained using the table in the appendix but in a little harder way. First take reciprocal of \(f\), which is

\(\frac{1}{f} = \frac{1}{{0.384}} = 2.61\)

and the degrees of freedom are now \(4\) and \(9\) (opposite of before). From the table you can notice that the one tailed value is a little bigger than \(0.1\)(thus two tailed is twice as big) and nearly \(0.2\)(it is known that is is equal to \(0.214\)as mentioned before).

However, since

\(P = 0.214 > 0.1 = \alpha \)

Do not reject null hypothesis at the given significance level. There is no statistical significant difference between the two standard deviations.

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