Answer:
The decision rule is
Reject the null hypothesis
The conclusion
There is sufficient evidence to conclude that mean daily consumption of regular-coffee drinkers greater than that of decaffeinated-coffee.
The p-value is [tex]p-value = 0.03682 [/tex]
Step-by-step explanation:
From the question we are told that
The first sample size is [tex]n_ 1 = 50[/tex]
The first sample mean is [tex]\=x_1 = 3.84[/tex]
The first sample standard deviation is [tex]s_1 = 1.26[/tex]
The second sample size is [tex]n_2 = 40[/tex]
The second sample mean is [tex]\=x_2 = 3.35 [/tex]
The second sample standard deviation is [tex]s_2 = 1.36[/tex]
The level of significance is [tex]\alpha = 0.05[/tex]
The null hypothesis is [tex]H_o : \mu_1 = \mu_2[/tex]
The alternative hypothesis is [tex]H_a : \mu_1 > \mu_2[/tex]
Generally the test hypothesis is mathematically represented as
[tex]t = \frac{( \= x_1 - \= x_2 ) - 0}{ \sqrt{ \frac{s^2_1 }{n_1} + \frac{s^2_2}{n_2} } }[/tex]
=> [tex]t = \frac{( 3.84 - 3.35 ) - 0}{ \sqrt{ \frac{1.26^2 }{50} + \frac{1.36^2}{40} } }[/tex]
=> [tex] t = 1.789 [/tex]
Generally the p-value is mathematically represented as
[tex]p-value = P(t > 1.789)[/tex]
From the z table
[tex]\Phi (1.789) = 0.03682[/tex]
So
[tex]p-value = P(t > 1.789) = 0.03682 [/tex]
From the value obtained we see that [tex]p-value < \alpha[/tex] hence
The decision rule is
Reject the null hypothesis
The conclusion
There is sufficient evidence to conclude that mean daily consumption of regular-coffee drinkers greater than that of decaffeinated-coffee
