Solution to Two groups of children were given visual acity tests,group.group 1 was composed of 11 children … - Sikademy
Author Image

Archangel Macsika

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

The Answer to the Question
is below this banner.

Can't find a solution anywhere?

NEED A FAST ANSWER TO ANY QUESTION OR ASSIGNMENT?

Get the Answers Now!

You will get a detailed answer to your question or assignment in the shortest time possible.

Here's the Solution to this Question

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


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

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


Based on the information provided, the significance level is \alpha = 0.05, and the degrees of freedom are 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 \alpha=0.05,df=23 degrees of freedom is t_c=2.068658.

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


s_p=\sqrt{\dfrac{(n_1-1)s_1^2+(n_2-1)s_2^2}{n_1+n_2-2}}

=\sqrt{\dfrac{(11-1)5^2+(14-1)6^2}{11+14-2}}

=5.587253

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


se=s_p\sqrt{\dfrac{1}{n_1}+\dfrac{1}{n_2}}=5.587253\sqrt{\dfrac{1}{11}+\dfrac{1}{14}}

=2.251168

Now, we finally compute the confidence interval:


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

=(26-21-2.068658\times 2.251168,

26-21+2.068658\times 2.251168)

=(0.3431,9.6569)

Therefore, based on the data provided, the 95% confidence interval for the difference between the population means \mu_1 - \mu_2 is 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).


Related Answers

Was this answer helpful?

Join our Community to stay in the know

Get updates for similar and other helpful Answers

Question ID: mtid-4-stid-46-sqid-2450-qpid-920