Research Methods - Biological Psychology Flashcards

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

What can you do with histograms?

A

Display your Frequencies

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

What are the rules with histograms?

A

X Axis must be labelled frequency
Bars are coded so we know the group of tallies they stand for
Bars to touch
Blank space where frequency = 0

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

What are descriptive statistics?

A

Analyse findings from a sample

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

What are inferential statistics?

A

How sample’s resuults relate back to the target population where the sample was drawn

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

Why are inferential statistics needed?

A

Are essential to see whether the results support the null hypothesis or rejecting it in favour of the alternative hypothesis

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

Define the Mann-Whitney U-Test

A

For ordinal level data / experiments with independent groups design

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

Define the Wilcoxon Test

A

For ordinal level data / experiments with repeated measures or matched pairs designss

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

Define the Spearman’s Rho

A

For ordinal level data / Used for correlations

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

Define Chi-Squared

A

For Nominal level data / Analysing independent variables in categories (i.e. most observations)

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

How do you decide which test to use?

A

Step 1) Figure out the level of data collected (if nominal then, use Chi Squared)

Step 2)Is the study a correlation or a test of difference?(if correlation, then, use Spearmann’s Rho)

Step 3)Is the data independent or related?
(if independent groups design, then Mann Whitney - if otherwise, then Wilcoxon)

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

How do you know is the data is nominal?

A

Data is nominal if researchers identify categories of response and simply count how many times they occur

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

How do you know if the data is ordinal?

A

Data is ordinal if responses can be ordered from highest to lowest

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

What the four levels of data collection?

A

Ratio level, interval level, ordinal level and nominal level data

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

What is ratio level data?

A

A score on a scale.

The most important part of the data is that there is a meaning score of 0 (no data) which gives it a starting point.

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

What is interval level data?

A

Also a score on a scale, but can go into negative figures (is used for things like temperature)
Has no fixed stating point

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

What is ordinal level data?

A

A number score representing rank position (i.e. league tables) and can be turned into interval/ratio data by putting scores into rank order)
It demolishes distinctions between rankings
More psychological measures gather interval/ratio level data,so ranking is a must.

17
Q

What is nominal level data?

A

Puts participants into categories (categorical data i.e. tally marks) to produce frequencies and is easily turned to percentages
Interval/ratio level data can be turned into nominal by putting data into a frequency table in order to turn it into a histogram.

18
Q

What is the basic procedure for all inferential tests?

A

1) Calculate your observed value: meant to be as small as possible but in the case of Spearman’s Rho, it is the opposite (big as possible)
2) Choose your probability level: As these tests work out the likely-hood of your results as normality of results = acceptance of null hypothesis or very unlikely = refuting null for alternative hypothesis as shows a pattern at work
3) Find your critical value (part 1):Once selected a value for P and calculated your observed value, can consider a critical value table (different table for directional and non-directional hypothesis)

4)Find your Value of n or df: these are scores that represent the size of your sample (n = numbers of participants and df = degrees of freedom)
The more df, the more categories

5)Find your critical values (part 2): Compare observed values with critical value (found when counting along the table) to see if statistically significant

(Mann Whitney & Wilcoxon - U =or < critical value then is statistically significant
Chi Squared & Spearman Rho- id r =or > critical value then is statistically significant)

19
Q

How unlikely do results have to be before you take them seriously and treat them as a pattern?

A

Decision summed up by P (probability)

P