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Sagot :
Using the z-distribution, as we have the standard deviation for the population, it is found that the sample provides enough evidence to conclude that self-esteem scores for these adolescents are significantly different from those of the general population.
What are the hypothesis tested?
At the null hypothesis, we test if the score for group-participation adolescents is the same as the general population, that is:
[tex]H_0: \mu = 50[/tex]
At the alternative hypothesis, we test if the score is different, that is:
[tex]H_1: \mu \neq 50[/tex]
What is the test statistic?
The test statistic is given by:
[tex]z = \frac{\overline{x} - \mu}{\frac{\sigma}{\sqrt{n}}}[/tex]
The parameters are:
- [tex]\overline{x}[/tex] is the sample mean.
- [tex]\mu[/tex] is the value tested at the null hypothesis.
- [tex]\sigma[/tex] is the standard deviation of the population.
- n is the sample size.
In this problem, we have that:
[tex]\overline{x} = 53.8, \mu = 50, \sigma = 15, n = 100[/tex].
Hence:
[tex]z = \frac{\overline{x} - \mu}{\frac{\sigma}{\sqrt{n}}}[/tex]
[tex]z = \frac{53.8 - 50}{\frac{15}{\sqrt{100}}}[/tex]
[tex]z = 2.53[/tex]
What is the decision?
Considering a two-tailed test, as we are testing if the mean is different of a value, with a significance level of 0.05, the critical value is [tex]|z^{\ast}| = 1.96[/tex]
Since the absolute value of the test statistic is greater than the critical value for the two-tailed test, it is found that the sample provides enough evidence to conclude that self-esteem scores for these adolescents are significantly different from those of the general population.
More can be learned about the z-distribution at https://brainly.com/question/26454209
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