Respuesta :
Answer:
Step-by-step explanation:
The mean SAT score is [tex]\mu=600[/tex], we are going to call it \mu since it's the "true" mean
The standard deviation (we are going to call it [tex]\sigma[/tex]) is
[tex]\sigma=48[/tex]
Next they draw a random sample of n=70 students, and they got a mean score (denoted by [tex]\bar x[/tex]) of [tex]\bar x=613[/tex]
The test then boils down to the question if the score of 613 obtained by the students in the sample is statistically bigger that the "true" mean of 600.
- So the Null Hypothesis [tex]H_0:\bar x \geq \mu[/tex]
- The alternative would be then the opposite [tex]H_0:\bar x < \mu[/tex]
The test statistic for this type of test takes the form
[tex]t=\frac{| \mu -\bar x |} {\sigma/\sqrt{n}}[/tex]
and this test statistic follows a normal distribution. This last part is quite important because it will tell us where to look for the critical value. The problem ask for a 0.05 significance level. Looking at the normal distribution table, the critical value that leaves .05% in the upper tail is 1.645.
With this we can then replace the values in the test statistic and compare it to the critical value of 1.645.
[tex]t=\frac{| \mu -\bar x |} {\sigma/\sqrt{n}}\\\\= \frac{| 600-613 |}{48/\sqrt(70}}\\\\= \frac{| 13 |}{48/8.367}\\\\= \frac{| 13 |}{5.737}\\\\=2.266\\[/tex]
since 2.266>1.645 we can reject the null hypothesis.
Answer:
The null hypothesis is that the SAT score is not significantly different for the course graduates.
Alternate hypothesis: there is a significant difference between the SAT score achieved by the course graduates as compared to the non-graduates.
Apply the t-test. The Test Statistic value comes out to be t = 1.738 and the p-value = 0.0844
Since the p-value is larger than 0.05, the evidence is weak and we fail to reject eh null hypothesis.
Hope that answers the question, have a great day!