Question #292198

Two groups of children were given visual acity tests,group.group 1 was composed of 11 children who receive their health care from private physician.the mean score for this group was 26 with standard deviation of 5.group 2 was composed of 14 children who receive their health care from the health department and had an average score of 21 with a standard deviation of assume normally distributed population with equal variance calculate the 95%confidence interval

1
Expert's answer
2022-01-31T16:27:04-0500

A F-test is used to test for the equality of variances. The following F-ratio is obtained:


F=s12s22=5262=0.694444F=\dfrac{s_1^2}{s_2^2}=\dfrac{5^2}{6^2}=0.694444

The critical values for df1=111=10,df2=141=13,α=0.05df_1=11-1=10,df_2=14-1=13, \alpha=0.05 are FL=0.2791,F_L = 0.2791, FU=3.2497,F_U=3.2497, and since F=0.694444,F = 0.694444, then the null hypothesis of equal variances is not rejected.


Based on the information provided, the significance level is α=0.05,\alpha = 0.05, and the degrees of freedom are df=n11+n21=111+141=23,df=n_1-1+n_2-1 = 11-1+14-1=23, assuming that the population variances are equal.

Hence, it is found that the critical value for this two-tailed test for α=0.05,df=23\alpha=0.05,df=23 degrees of freedom is tc=2.068658.t_c=2.068658.

Since the population variances are assumed to be equal, we need to compute the pooled standard deviation, as follows:


sp=(n11)s12+(n21)s22n1+n22s_p=\sqrt{\dfrac{(n_1-1)s_1^2+(n_2-1)s_2^2}{n_1+n_2-2}}

=(111)52+(141)6211+142=\sqrt{\dfrac{(11-1)5^2+(14-1)6^2}{11+14-2}}

=5.587253=5.587253

Since we assume that the population variances are equal, the standard error is computed as follows:


se=sp1n1+1n2=5.587253111+114se=s_p\sqrt{\dfrac{1}{n_1}+\dfrac{1}{n_2}}=5.587253\sqrt{\dfrac{1}{11}+\dfrac{1}{14}}

=2.251168=2.251168

Now, we finally compute the confidence interval:


CI=(x1ˉx2ˉtc×se,x1ˉx2ˉ+tc×se)CI=(\bar{x_1}-\bar{x_2}-t_c\times se, \bar{x_1}-\bar{x_2}+t_c\times se)

=(26212.068658×2.251168,=(26-21-2.068658\times 2.251168,

2621+2.068658×2.251168)26-21+2.068658\times 2.251168)

=(0.3431,9.6569)=(0.3431,9.6569)

Therefore, based on the data provided, the 95% confidence interval for the difference between the population means μ1μ2\mu_1 - \mu_2 is 0.3431<μ1μ2<9.6569,0.343 1< \mu_1 - \mu_2 < 9.6569, which indicates that we are 95% confident that the true difference between population means is contained by the interval (0.3431,9.6569).(0.3431, 9.6569).




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