Chapter 6

Question 1

Null Hypothesis

Answer 1

The null hypothesis H0 skeptically argues that data come from a boring population describes by the null model
This is a statement of no effect or no difference. It assumes that any observed results are purely due to chance.

Question 2

What is the key to hypothesis testing?

Answer 2

Building a sampling distribution from the appropriate null model is key to hypothesis testing.

Question 3

What is hypothesis testing?

Answer 3

Hypothesis testing compare data to what we would expect to see if a specific null hypothesis were true. If the data are too unusual, compared to what we would expect to see if the null hypothesis were true then the null hypothesis is rejected

Question 4

Null hypothesis

Answer 4

A specific statement about a population made for the sake of argument (aka H0 the skeptical view)

Question 5

Alternative hypothesis

Answer 5

All parameter values except the null (aka Ha or H1)

Question 6

Are null hypothesis specific?

Answer 6

Yes, this means that the null hypothesis specifies a model that can generate a sampling distribution eg. mu = 0, Variance = 1

Question 7

Are alternative hypothesis specific?

Answer 7

No, they are less specific because we can’t generate a sampling distribution from Ha. Every possible value for a population characteristic or contrast is included, except that specified the null hypothesis.

Question 8

P-value

Answer 8

The P value is the probability a sample from the null model would be as or more extreme than out sample.
This is a probability value that indicates how likely the observed results would occur if the null hypothesis were true. A low p-value (typically below 0.05) suggests that the observed results are unlikely to be due to chance, leading to the rejection of the null hypothesis in favor of the alternative hypothesis.

Question 9

Most test are two tailed

Answer 9

This means that a deviation in either tail of the distribution would be worth reporting. The alternative hypothesis is two sided, this just means that the alternative hypothesis allows two possibilities: that p is greater than 0.0 or that p is less than 0.0

Question 10

One tailed P-values

Answer 10

If one tail is of a distribution is not meaningful, report a P-value without it
P-value <= 0.05: null hypothesis is rejected
P-value > 0.05: null hypothesis is not rejected

Question 11

Statistical Significance

Answer 11

The significance level, a, is the probability used as the criterion for rejecting the null hypothesis

Question 12

False Positive: Rejecting a true null

Answer 12

Type 1 Error
The significance level, a, gives us the probability of committing a this error. If we go along with convention and use a significance level of a = 0.05, then we reject H0 whenever P is less than or equal to 0.05. This means that, if the null hypothesis were true, we would reject it mistakenly one time in 20.

Question 13

False Negative: Failing to reject a false null

Answer 13

Type ll Error
If a null hypothesis is false, we need to reject it to get the right answer. Failure to reject a false null hypothesis is a this type of error.