Hypothesis testing

Question 1

what’s a p value?

Answer 1

The P​-value is the probability of getting a value of the test statistic that is at least as extreme as the one representing the sample​ data, assuming that the null hypothesis is true.

Question 2

What is a type 1 error?

Answer 2

rejecting a true null hypothesis

Question 3

what is a type 2 error?

Answer 3

failing to reject a false null hypothesis

Question 4

Can type 1 and type 2 errors occur at the same time?

Answer 4

NO. Type 1 only occurs when H0 is true. Type 2 only occurs when H0 is false.

Question 5

what is the null hypothesis always about?

Answer 5

a population parameter, can refer to a status quo, historical value or just a relevant value to the test

Question 6

can a null hypothesis ever be proven/accepted?

Answer 6

NOOOOO. It may or may not be rejected

Question 7

what does the alternative hypothesis do?

Answer 7

challenges H0 in some way–> it’s usually what you’re trying to find, as this can be proven

Question 8

Steps for a critical value approach to testing the null hypothesis

Answer 8

1. State H0, H1
2. Choose level of significance & sample size
3. Determine test statistics (tstat or Z stat) + sampling distribution (must assume approximate normality/ n>=30)
4. Determine critical values and ID rejection region + non rejection region
5. Collect data & compute test statistic value
6. Make statistical decision & managerial conclusion

Question 9

P value approach to hypothesis testing

Answer 9

1. State H0, H1
2. Choose level of significance & sample size
3. Determine appropriate test statistics (tstat or Z stat) + sampling distribution (must assume approximate normality/ n>=30)
4. Collect data and compute test stat value and associate p value
5. Make the statistical decision & state the managerial conclusion (if P

Question 10

What are the critical values in the hypothesis test dependant on?

Answer 10

the level of significance (the alpha)