Respuesta :
The diet which is developed by the nutritionist is effective at the 0.05 level of significance. Claim is agreed.
When do we use two-sample t-test?
The two-sample t-test is used to determine if two population means are equal.
A nutritionist has developed a diet that she claims will help people lose weight. In this,
- Twelve people were randomly selected to try the diet.
- Their weights were recorded prior to beginning the diet and again after 6 months.
Here are the original weights, in pounds, with the weight after 6 months in parentheses.
- Before 192 212 171 215 180 207 165 168 190 184 200 196
- After 183 196 174 211 160 191 162 175 190 179 189 195
The mean of the weights before 6 moths is,
[tex]\overline X_1=\dfrac{192+ 212 +171 +215 +180 +207 +165 +168 +190 +184 +200 +196 }{12}\\\overline X_1=190[/tex]
The mean of the weights after 6 months is,
[tex]\overline X_2=\dfrac{ 183 +196 +174 +211 +160 +191 +162 +175 +190 +179 +189 +195 }{12}\\\overline X_1=183.75[/tex]
Standard deviation of both the data is 16.9 and 14.7.
1. Null and Alternative Hypotheses.
The following null and alternative hypotheses need to be tested:
[tex]\begin{array}{ccl} H_0: \mu_1 & = & \mu_2 \\\\ \\\\ H_a: \mu_1 & > & \mu_2 \end{array}[/tex]
This corresponds to a right-tailed test, for which a t-test for two population means, with two independent samples, with unknown population standard deviations will be used.
- (2) Rejection Region
Based on the information provided, the significance level is α=0.05 and the degrees of freedom are df = 22. In fact, the degrees of freedom are computed as follows, assuming that the population variances are equal:
[tex]df_{Total} = df_1 + df_2 = 11 + 11 = 22[/tex]
Hence, it is found that the critical value for this right-tailed test is
[tex]t_c=1.717[/tex], for α=0.05 and df=22
The rejection region for this right-tailed test is,
[tex]R = \{t: t > 1.717\}[/tex]
(3) Test Statistics
Since it is assumed that the population variances are equal, the t-statistic is computed as follows:
[tex]t = \displaystyle \frac{\bar X_1 - \bar X_2}{\sqrt{ \frac{(n_1-1)s_1^2 + (n_2-1)s_2^2}{n_1+n_2-2}(\frac{1}{n_1}+\frac{1}{n_2}) } }[/tex]
[tex]\displaystyle \frac{ 190 - 183.75}{\sqrt{ \frac{(12-1)16.9^2 + (12-1)14.7^2}{ 12+12-2}(\frac{1}{ 12}+\frac{1}{ 12}) } } = 0.967[/tex]
- (4) Decision about the null hypothesis
Since it is observed that t=0.967≤tc=1.717 it is then concluded that the null hypothesis is not rejected.
Using the P-value approach: The p-value is p=0.1721 and since p=0.1721≥0.05p = 0.1721 it is concluded that the null hypothesis is not rejected.
(5) Conclusion
It is concluded that the null hypothesis H₀ is not rejected. Therefore, there is not enough evidence to claim that the population mean μ1 is greater than μ2, at the α=0.05 significance level.
Confidence Interval
The 95% confidence interval is −7.16<μ<19.66
Thus, the diet which is developed by the nutritionist is effective at the 0.05 level of significance. Claim is agreed.
Learn more about the two-sample t-test here;
https://brainly.com/question/27198724
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