A teacher conducted a study to know if blended leaming improves the students performances. A class of 25 students of Grade 11 was surveyed and found out that their mean score was 83 with a standard deviation of 3. A
study from other country revealed that = 80 with a standard deviation of 4. Test the hypothesis at 0.10 level of significance.
Difference of two independent normal variables
Let "X" have a normal distribution with mean "\\mu_X" and variance "\\sigma_X^2."
Let "Y" have a normal distribution with mean "\\mu_Y" and variance "\\sigma_Y^2."
If "X" and "Y"are independent, then "X-Y"will follow a normal distribution with mean "\\mu_X-\\mu_Y" and variance "\\sigma_X^2+\\sigma_Y^2."
"\\mu_{X-Y}=83-80=3""s_{X-Y}=\\sqrt{(3)^2+(4)^2}=5"The following null and alternative hypotheses need to be tested:
"H_0:\\mu=0"
"H_1:\\mu\\not=0"
This corresponds to a two-tailed test, for which a t-test for one mean, with unknown population standard deviation, using the sample standard deviation, will be used.
Based on the information provided, the significance level is "\\alpha=0.01,"
"df=n-1=25-1=24" degrees of freedom, and the critical value for a two-tailed test is "t_c=2.79694."
The rejection region for this two-tailed test is "R=\\{t:|t|>2.79694\\}"
The t-statistic is computed as follows:
Since it is observed that "|t|=0.12<2.79694=t_c," it is then concluded that the null hypothesis is not rejected.
Using the P-value approach:
The p-value for two-tailed "\\alpha=0.01," "df=24, t=0.12" is "p=0.001071," and since "p=0.905482>0.01=\\alpha," it is then concluded that the null hypothesis is not rejected.
Therefore, there is not enough evidence to claim that the population mean "\\mu" is different than 0, at the "\\alpha=0.01" significance level.
Therefore, there is not enough evidence to claim that blended leaming improves the students performances, at the "\\alpha=0.01" significance level.
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