Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

PS1813 - 2 - The Spine of Statistics > 2.9. - Null hypothesis testing > Flashcards

2.9. - Null hypothesis testing Flashcards

1
Q

Who came up with the idea of p-values?

A

Fisher

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Who believed that there are 2 competing hypotheses?

A

Neyman and Pearson

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

What are 2 competing hypotheses?

A

Alternative hypothesis

Null hypothesis

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

What symbols represent the alternative hypothesis?

A

H1

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

What symbols represent the null hypothesis?

A

Ho

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

What does an alternative hypothesis state?

A

States that there will be a difference in outcome

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

What does a null hypothesis state?

A

States that there won’t be a difference in outcome

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

What are 2 types of alternative hypothesis?

A

Directional

Non-directional

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

What is a directional hypothesis also called?

A

One-tailed hypothesis

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

What is a non-directional hypothesis called?

A

Two-tailed hypothesis

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

What does NHST stand for?

A

Null Hypothesis Significance Testing

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

What is a test statistic?

A

A statistic for which we know how frequently different values occur

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

How do we calculate test statistic?

A

effect / error
variance explained by model / variance not explained by model
signal / noise

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

What is the cut-off point for confidence?

A

0.05, or 5%

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

What does it mean if p is less than .05?

A

The test statistic is significant and we reject the null hypothesis

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Who identified type I and type II errors?

A

Neyman and Pearson

17
Q

What is another name for a type I error?

A

False posItIve

18
Q

When do type I errors occur?

A

When we think we found something, but in reality there was no effect. We wrongly reject the null hypothesis

19
Q

What is the value of alpha?

A

Usually 0.05

20
Q

What does the value of 0.05 probability mean?

A

If we replicated our data collection where we found no error 100 times, we could expect that 5/100 times we would obtain a significant test statistic. We only make a type I error 5% of the time.

21
Q

What is another name for a type II error?

A

False negative

22
Q

When do type II errors occur?

A

When we believe that there is no effect, when actually there is. We wrongly accept the null hypothesis

23
Q

What did Cohen suggest?

A

The maximum acceptable probability of a type II error is 0.2. This is known as beta.

24
Q

What does 0.2 probability mean when looking at type II errors?

A

20/100 times we would fail to detect effects in the population

25
Q

What factors affect the value of beta?

A

Strength of effect, type of design, sample size

26
Q

Who decides the value of alpha?

A

The researcher

27
Q

What does the term familywise error mean?

A

The increase in error rate across several statistical tests conducted on the same data.

28
Q

How do we calculate the familywise error?

A

1 - 0.95 to the power of the number of tests carried out on the data

29
Q

What is another name for familywise error?

A

Experimentwise error

30
Q

How do we prevent an increase in error rate between several statistical tests?

A

Adjust the level of significance by dividing the value of alpha by the number of comparisons

31
Q

Define statistical power

A

The ability of a test to find an effect

32
Q

How do we calculate statistical power?

A

1 - beta

33
Q

What is the general value for beta?

A

0.2

34
Q

What power do we aim to achieve?

A

0.8

35
Q

What does a power of 0.8 suggest?

A

0.8 is significant. Equates to an 80% chance of detecting an effect if one genuinely exists

36
Q

What factors affect the power of a statistical test?

A

How big the effect is
How strict we are about deciding if an effect is significant
Sample size

37
Q

What affect does the sample size have on the amount of sampling error?

A

The larger the sample, the less sampling error there will be

PS1813 - 2 - The Spine of Statistics (5 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions