More than 200,000 people worldwide take the GMAT examination each year as they apply for MBA programs. Their scores vary normally with mean about u= 525 and standard deviation about sigma= 100. One hundred students go through a rigorous training program designed to raise their GMAT scores. Test the hypotheses H sub 0: u= 525 H sub A: u > 525 in each of the following situations: a) The students' score is x = 541.4. Is this result significant at the 5% level? b) The average score is x = 541.5. Is this result significant at the 5% level? c) What conclusions may you draw by comparing the answers to parts a and b?
@jim_thompson5910 can you help please
what do you have so far?
A) z=(x-u)/(SD/sqrt(n)) z=(541.4-525)/100sqrt(100)) z=1.64 look up z=1.64 to find .4495 .5+.4495=.9495 since .9495<.95 we cannot reject null hypothesis
The alternate hypothesis is mu > 525 so this is a right tailed test
yes
what is P(Z > 1.64) equal to?
0.0505?
correct
b) The average score is x = 541.5. Is this result significant at the 5% level? since \[\Large P(Z > 1.64) = P(X > 541.5) \approx 0.0505\] this means (p-value) > alpha where alpha = 0.05 in this case. Because (p-value) > alpha is true, we fail to reject the null. Because the p value isn't really small, it's not statistically significant
okay so thats it for b? moving to c now?
yes you just need to do a and c
the work you have applies to part b
a) P{X>541.4}=P{Z>z}, z=(541.4-525)/100=0.164; P{}=0.44
i'm getting p-value = 0.4349 but p-value = 0.44 works too
so for part a) we're failing to reject the null and the result is not statistically significant
yes
what conclusions can we draw?
that the null is correct, Their scores vary normally with mean approx 525 (with sd 100) not greater?
we haven't proven the null to be correct. We just can't reject it based on this evidence
so fix that to say *we don't have the evidence to prove the null is correct, so from what we have their scores typically vary with mean approx 525 not greater
the p values were larger than alpha = 0.05 which is why we fail to reject the null failing to reject the null is not the same as proving the null is 100% true
but in a way, it's like concluding the null is true
okay so this is what I have for my answer: A) P = 44, we're failing to reject the null and the result is not statistically significant B) P(Z>1.64)=P(X>541.5) = 0.0505 we fail to reject the null. Because the p value isn't really small, it's not statistically significant C) we don't have the evidence to prove the null is correct, so from what we have their scores typically vary with mean approx 525 not greater
P = 44 is not the pvalue for a
also, make sure to state the answer in your own words
.44* and yes i will transpose it when writing it down
? is that good @jim_thompson5910
I don't agree with what you wrote for c
the p values were larger than alpha = 0.05 which is why we fail to reject the null failing to reject the null is not the same as proving the null is 100% true (but in a way, it's like concluding the null is true)
so all we would say was that we fail to reject the null simply because there is no evidence?
er not enough evidence to prove it wrong
so we can say something like we fail to reject the null which means we have no choice but to accept that the mean score is 525
more stats testing would have to be done
oh okay got it
thank you! @jim_thompson5910
you're welcome
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