The pooled estimate of the variance is 187.650 and the test statistic is -2.32
The dataset is given as:
Regular price 138 124 89 112 116 123 98
Reduced price 124 134 154 135 118 126 133 132
Let the regular price be dataset 1 and the reduced price be dataset 2.
So, we have:
#1: 138 124 89 112 116 123 98
#2: 124 134 154 135 118 126 133 132
Calculate the sample means and the sample standard deviations using a graphing calculator.
#1
[tex]\sigma_1 = 16.56[/tex]
[tex]\bar x_1 = 114.29[/tex]
[tex]\sigma_1^2 = 274.24[/tex]
#2
[tex]\sigma_2 = 10.65[/tex]
[tex]\bar x_2 = 132[/tex]
[tex]\sigma_2^2 = 113.43[/tex]
The pooled estimate of the variance is:
[tex]\sigma_p^2 = \frac{\sigma_1^2(n_1 - 1) + \sigma_2^2(n_2 - 1)}{(n_1 - 1) + (n_2 - 1)}[/tex]
This gives
[tex]\sigma_p^2 = \frac{274.24 * (7 - 1) + 113.43 * (8 - 1)}{(7- 1) + (8- 1)}[/tex]
Evaluate the factors
[tex]\sigma_p^2 = \frac{2439.45}{13}[/tex]
Divide
[tex]\sigma_p^2 = 187.65[/tex]
Hence, the pooled estimate of the variance is 187.650
This is calculated using:
[tex]t = \frac{\bar x_1 - \bar x_2}{\sqrt{\sigma_p^2} * \sqrt{\frac{1}{n_1} + \frac{1}{n_2}}}[/tex]
This gives
[tex]t = \frac{114.29 - 132}{\sqrt{187.650} * \sqrt{\frac{1}{7} + \frac{1}{6}}}[/tex]
This gives
[tex]t = \frac{-17.71}{\sqrt{187.650} * \sqrt{\frac{13}{42}}}[/tex]
Evaluate the product
[tex]t = \frac{-17.71}{\sqrt{58.08214}}[/tex]
Evaluate the exponent
[tex]t = \frac{-17.71}{7.62}[/tex]
Divide
t = -2.32
Hence, the test statistic is -2.32
The critical value at 0.025 significance level is -1.96
-2.32 is less than -1.96
This means that we accept the null hypothesis
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