Null Hypothesis And Significance Testing

Question 1

What is a null hypothesis ? (Ho)

Answer 1

A hypothesis that states there will be no difference in the data

Question 2

What is an alternative hypothesis? (Ha)

Answer 2

a statement that suggests there will be a relationship or a difference in the data

Question 3

What is Null hypothesis significant testing? (NHST)

Answer 3

A methods of statistical inferences.

Which involves turning a research question into two hypothesis.

A null hypotheses and an alternative hypothesis.

Question 4

When is a null hypothesis considered to be true?

Answer 4

It is considered to be true until there is no evidence against it.

Question 5

What type of hypothesis are we attempting to find evidence for?

Answer 5

Alternative hypothesis.

Question 6

What is a one tailed hypothesis?

Answer 6

State which direction the effect, differences or association will be in.

Question 7

What is a two tailed hypothesis?

Answer 7

Do not state the direction of the effect or association will be in.

Question 8

What type of data can we only collect withe nominal level data?

Answer 8

Frequencies

Question 9

How are descriptive statistics presented?

Answer 9

As frequencies.

Question 10

What is chi square and what does it asses?

Answer 10

An inferential statistical test that is used for nominal level data.

It assesses if there is an association between categorical variables.

Question 11

How do we estimate expected frequencies (which categories we would expect people to fall into by chance?

Answer 11

(Row total) x (column total) Divided by N

Question 12

What does the chi squared test do?

Answer 12

Measures the discrepancy between observed frequencies and expected frequencies.

Question 13

What results need to show from a chi squared test to show there is an association between the IV and DV?
Also an association between two categorical variables ?

Answer 13

Observed frequencies need to differ largely enough from expected frequencies.

Question 14

What does the type of chi square test depend on?

Answer 14

-Number of rows and columns

Question 15

What does every statistical test have?

Answer 15

Assumptions.

Question 16

What are the assumptions for in statistical tests?

Answer 16

Rules that our data must adhere to in order to be analysed using that test.

We look at our data then make a decision based on certain criteria.

Question 17

What are the assumptions for chi square?

Answer 17

1. Independence - all frequencies must unique. This means it cannot be used for within subjects/repeated measures designs.
2. All expected values should be above 5

If there is lots of conditions all expected values should be greater or equal to 1 And no more than 20% of expected counts should be less than 5.

Sample size is important we need to have an appropriate number of data points. But if it is too large this can lead to misleading results.

Question 18

What are P values?

Answer 18

They evaluate how the well the data in the sample supports the argument that the null hypothesis is true.

Question 19

What do High P values indicate?

Answer 19

Data is likely with a true null

Question 20

What do low P values indicate?

Answer 20

Data is unlikely with a true null.

Question 21

What can we do to the null hypothesis if there is a low P value?

Answer 21

Reject the null hypothesis.

Question 22

What is the P value in technical terms?

Answer 22

A p value is the probability of obtaining an effect at least as extreme as the one in your sample data, assuming the truth of your null hypothesis.

Question 23

General rules of P values?

Answer 23

If P value is below 0.5 it is statistically significant.

The level at which we accept a result t o be significant is known as the alpha level (a)

Question 24

What is a test statistic for?

Answer 24

Let’s the reader know which statistical test was conducted.

Question 25

What is the the test statistic for chi square?

Answer 25

Chi symbol and a squared symbol

X2

Question 26

What does the effect size tell us when using chi squared?

Answer 26

How strong an association is between two variables.

Question 27

What type of effect size would we use for 2x2 chi square?

Answer 27

Phi

Question 28

What effect size would we report for other chi squared designs?

Answer 28

Cramer’s V.

Question 29

What problems are there with NHST?

Answer 29

Type 1 and type 2 errors

Question 30

What is a type 1 error?

Answer 30

Rejection of a true null hypothesis (Finding a false positive)

Question 31

What is a type 2 error?

Answer 31

Failing to reject a null hypothesis (known as a false negative)

Question 32

What is the problem of running to many statistical tests?

Answer 32

Increase the chances of a type 1 error occurring.

Question 33

How do we prevent a type 1 error occurring?

Answer 33

Change the alpha level and divide the alpha level (0.05) by the amount of tests you conduct. (Bonferroni correction)

Question 34

What is P hacking?

Answer 34

A method of manipulating data to achieve significant results by conducting multiple inferential statistical tests.

Omitting other information

Changing the DV

Stopping to gather data when you have significant result.

Question 35

How can we stop P hacking?

Answer 35

Preregistration and moving the alpha level down to 0.005 instead of 0.05