A two-sample t-test for a difference in means will be conducted to investigate whether the average amount of money spent per customer at Department Store M is different from that at Department Store V. From a random sample of 35 customers at Store M, the average amount spent was $300 with standard deviation $40. From a random sample of 40 customers at Store V, the average amount spent was $290 with standard deviation $35. Assuming a null hypothesis of no difference in population means, what is the test statistic for the appropriate test to investigate whether there is a difference in population means?

The test statistic is 1.145 for the appropriate test to investigate whether there is a difference in population means.

A test statistic is a numerical value calculated from sample data in hypothesis testing.

Given that

Sample 1: Store M

Sample size, [tex]n_1[/tex] = 35,

Sample mean, [tex]\bar{X_1}[/tex] = 300,

Standard deviation, [tex]s_1[/tex] = 40.

Sample 2: Store V

Sample size, [tex]n_2[/tex] = 40,

Sample mean, [tex]\bar{X_2}[/tex] = 290,

Standard deviation, [tex]s_2[/tex] = 35.

The null hypothesis, [tex]H_o[/tex] : there is no difference in population means, i.e.,

[tex]\mu_1 =\mu_2[/tex].

The alternate hypothesis, [tex]H_1[/tex] : there is a significant difference in population means, i.e.,

[tex]\mu_1 \neq\mu_2[/tex].

Under the null hypothesis, the test statistic is

[tex]t = \dfrac{\bar{X_1}-\bar{X_2}}{\sqrt{\frac{s_1^2}{n_1}+\frac{s_2^2}{n_2} }}[/tex]

  [tex]= \dfrac{300-290}{\sqrt{\frac{40^2}{35}+\frac{35^2}{40} }}\\=\dfrac{10}{\sqrt{\frac{1600}{35}+\frac{1225}{40} }} \\=\dfrac{10}{\sqrt{45.714+30.625 }} \\=\dfrac{10}{\sqrt{76.339 }}\\=\dfrac{10}{8.737}\\=1.145[/tex]

Hence the test statistic is 1.145.

Learn more about test statistics here:

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