A random sample of five pairs of observations were selected, one of each pair from a population with mean\({\mu _2}\), the other from a population with mean \({\mu _2}\).The data are shown in the accompanying table.

Pair

Value from population 1

Value from population 2

1

28

22

2

31

27

3

24

20

4

30

27

5

22

20

a. Test the null hypothesis \({H_0}:{\mu _d} = 0\) against\({H_0}:{\mu _d} \ne 0\), where\({\mu _d} = {\mu _1} - {\mu _2}\) . Compare \(\alpha = 0.05\)with the p-value of the test.

Short Answer

Expert verified

a. There is no sufficient evidence to claim that the difference of the mean pairs is zero.

Step by step solution

01

Given information

The number of pairs, \({n_d} = 5\).

The data set is given as follows:

Pair

Value from population 1

Value from population 2

1

28

22

2

31

27

3

24

20

4

30

27

5

22

20

02

State the paired difference test of hypothesis for \({\mu _d}.\)

The Student’s t-test statistic for the small sample is,

\(t = \frac{{\bar d - {D_0}}}{{{s_d}/\sqrt {{n_d}} }}\)

Where \(\bar d\) is the sample mean difference, \({s_d}\) is the sample standard deviation difference, and \({n_d}\) is the number of pairs.

03

Compute the mean and standard deviation of the given data set.

A random sample of five pairs of observations were selected, one of each pair from a population with\({\mu _1}\) and other with mean\({\mu _2}\).

The calculation table is given as follows:

Values from population 1

\(\left( {{x_i}} \right)\)

Values from population 2

\(\left( {{y_i}} \right)\)

\({d_i} = {x_i} - {y_i}\)

\(d_i^2\)

28

22

6

36

31

27

4

16

24

20

4

16

30

27

3

9

22

20

2

4

\(\sum\limits_{i = 1}^5 {{d_i}} = 19\)

\(\sum\limits_{i = 1}^5 {d_i^2} = 81\)

The mean of the difference of the two population is computed as follows:

\(\begin{aligned}{c}\bar d &= \frac{{\sum {{d_i}} }}{{{n_d}}}\\ &= \frac{{19}}{5}\\ &= 3.8\end{aligned}\)

The standard deviation of the difference of the two population is computed as follows:

\(\begin{aligned}{c}{s_d} &= \sqrt {\frac{1}{{\left( {{n_d} - 1} \right)}}\left( {\sum {d_i^2} - \frac{{{{\left( {\sum {{d_i}} } \right)}^2}}}{{{n_d}}}} \right)} \\ &= \sqrt {\frac{1}{{\left( {5 - 1} \right)}}\left( {81 - \frac{{{{\left( {19} \right)}^2}}}{5}} \right)} \\ &= \sqrt {\frac{1}{4}\left( {81 - 72.2} \right)} \\ &= \sqrt {2.2} \\ &= 1.48\end{aligned}\)

Thus, the mean is 3.8 and the standard deviation is 1.48.

04

Compute the test of the null hypothesis \({H_0}:{\mu _d} = 0\) against\({H_0}:{\mu _d} \ne 0\).

a.

The null and alternative hypothesis are:

\(\begin{aligned}{l}{H_0}:{\mu _d} &= 0\\{H_a}:{\mu _d} \ne 0\end{aligned}\)

The significance level is, \(\alpha = 0.05.\)

The test statistic is computed as:

\(\begin{aligned}{c}t &= \frac{{\bar d - {D_0}}}{{{s_d}/\sqrt {{n_d}} }}\\ &= \frac{{3.8 - 0}}{{1.48/\sqrt 5 }}\\ &= \frac{{3.8}}{{0.662}}\\ &= 5.7412\end{aligned}\)

This is a two-tailed test. The rejection region is, \(|t| > {t_{\frac{\alpha }{2}}}\).

The degree of freedom is computed as:

\(\begin{aligned}{c}\left( {n - 1} \right) &= \left( {5 - 1} \right)\\ &= 4\end{aligned}\)

The \({t_{\frac{\alpha }{2}}}\) value with \(\alpha = 0.05\) corresponding to the degree of freedom 4 obtained from the t-table is 2.776.

Here, \(|t| > {t_{\frac{\alpha }{2}}} \Rightarrow |5.7412| > 2.776.\) So, we reject the null hypothesis.

Hence, there is no sufficient evidence to claim that the difference of the mean pairs is zero.

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