A lecturer wants to know if his statistics class has a good grasp of basic maths from matric level. Eleven students are chosen at random from the class and given a maths proficiency test. The lecturer wants the class to be able to score above 75 on the test to show that they had a good grasp of basic maths. The eleven students get scores shown below: 62 88 71 50 67 70 92 75 68 83 95 Can the lecturer be 95 percent confident that the students had a good grasp of basic maths?
"s^2=\\dfrac{\\sum_i(x_i-\\bar{x})^2}{n-1}=\\dfrac{1}{11-1}((62-\\dfrac{821}{11})^2"
"+(88-\\dfrac{821}{11})^2+(71-\\dfrac{821}{11})^2+(50-\\dfrac{821}{11})^2"
"+(67-\\dfrac{821}{11})^2+(70-\\dfrac{821}{11})^2+(92-\\dfrac{821}{11})^2"
"+(75-\\dfrac{821}{11})^2+(68-\\dfrac{821}{11})^2+(83-\\dfrac{821}{11})^2"
"+(95-\\dfrac{821}{11})^2=186.854545"
"s=\\sqrt{s^2}=13.6695"
The following null and alternative hypotheses need to be tested:
"H_0:\\mu\\leq75"
"H_1:\\mu>75"
This corresponds to a right-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=0.05,"
"df=n-1=11-1=10" degrees of freedom, and the critical value for a right-tailed test is"t_c= 1.812461."
The rejection region for this right-tailed test is "R=\\{t:t>1.812461\\}."
The t-statistic is computed as follows:
Since it is observed that "t=-0.088223<1.812461=t_c," it is then concluded that the null hypothesis is not rejected.
Using the P-value approach: The p-value for right-tailed, "\\alpha=0.05, df=10,"
"t=-0.088223" is"p=0.534279," and since "p=0.534279>0.05=\\alpha," it is concluded that the null hypothesis is not rejected
Therefore, there is not enough evidence to claim that the population mean "\\mu" is greater than 75, at the "\\alpha=0.05" significance level.
Therefore, there is not enough evidence to claim that the students had a good grasp of basic maths, at the "\\alpha=0.05" significance level.
1.3 The sample proportion is computed as follows, based on the sample size "n=200" and the number of favorable cases "X=120"
"\\hat{p}=\\dfrac{X}{n}=\\dfrac{120}{200}=0.6"The critical value for "\\alpha=0.025" is "z_c=z_{1-\\alpha\/2}=2.2414."
The corresponding confidence interval is computed as shown below:
"\\hat{p}+z_c\\times\\sqrt{\\dfrac{\\hat{p}(1-\\hat{p})}{n}}\\bigg)"
"=\\bigg(0.6-2.2414\\times\\sqrt{\\dfrac{0.6(1-0.6)}{200}},"
"0.6+2.2414\\times\\sqrt{\\dfrac{0.6(1-0.6)}{200}}\\bigg)"
"=(0.5224, 0.6776)"
Therefore, based on the data provided, the 97.5% confidence interval for the population proportion is "0.5224<p<0.6776," which indicates that we are 97.5% confident that the true population proportion "p" is contained by the interval "(0.5224, 0.6776)."
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