1.20 Year 2 Research Methods - Probability and Significance Flashcards

You may prefer our related Brainscape-certified flashcards:
1
Q

Experimental Hypothesis

A

Non-Direction or Directions, one or the other is accepted

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

Null Hypothesis

A

State there will be no change in the conditions

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

Probability

A

Likelihood a certain event will occur, 0 means statistically impossible whereas 1 in statistically certain. This is written as a percentage represented as a decimal

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

Significance

A

How certain we are a difference or correlations exists, if a result is significant then the researcher can reject the Null and accept the experimental

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

Accepted level of significance is Psychology

A

P≤0.05 meaning there is a less than 5% chance the findings are due to chance. : P≤0.01 used when there is a possible human cost e.g. in a drug trail

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

Calculated Value (CV)

A

Result that has been calculated from the stats test, which is compared to the critical value.

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

Critical Value

A

Allows us to work out whether result is significant or not, and which hypothesis to accept, found in CV table. If significant we accept experimental hypothesis and vice versa.

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

Primary Data

A

Data researcher has found themselves

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

Secondary Data

A

Data researcher has found from another source

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

Meta-Analysis

A

Uses secondary data across multiple studies and analyses

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

The CV must be EQUAL or LESS than the CV to be significant when using

A
  • Sign Test
  • Mann Whitney U
  • Wilcoxon
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

The CV must be EQUAL to or MORE than the CV to be significant when using

A
  • Chi Squared
  • Pearson’s R
  • Spearman’s Rho
  • Unrelated T-Test
  • Related T-Test
    Remember: RULE OF ‘R’
    : Stats test with letter R means the CV must be MORE than the CV
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Mean (Central Tendency)

A

Add all values and divide by the number of values

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

Strengths of Mean

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

Limitations of Mean

A
  • Still impacted by anomalies
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Median (Central Tendency)

A

All values lined up and middle value picked

17
Q

Strengths of Median

A
  • No anomalies
18
Q

Limitations of median

A
  • Unrepresentative
19
Q

Mode (Central Tendency)

A

Value used the most

20
Q

Strengths of Mode

A
  • No anomalies
21
Q

Limitations of Mode

A
  • Unrepresentative
22
Q

Range (Dispersion)

A

Difference between lowest and highest results

23
Q

Strengths of range

A

None

24
Q

Limitations of range

A
  • Impacted by anomalies
25
Q

Standard Deviation (Dispersion)

A

Smaller the numbers the less it differs from mean

26
Q

Strengths of Standard Deviations

A
  • Thorough Analysis
27
Q

Limitations of standard deviation

A

None

28
Q

Type 1 Error

A

Most common. When researcher accidentally rejects the wrong hypothesis. Researcher thought they found a significant difference or correlation when they hadn’t – known as ‘false positive’ or optimistic error. Likely to occur when researcher is being too lenient

29
Q

Type 2 Error

A

When a researcher accepts the null when it should have been rejected. Researcher thinks they didn’t find a significant difference when they did – known as a false negative or pessimistic error. Likely to occur when researcher is too strict