1. Data analysis
Research methods

2. Data analysis 2 step process Descriptive statistics
Measures of central tendency, graphs and measures of dispersion
Inferential statistics
Use of statistical tests

3. Descriptive stats Measures of central tendency Mean, mode, median
Their strengths & weaknesses
Measures of dispersion
Standard deviation (measure of how spread the data is from the mean) and range

4. Inferential stats
Must know how to carry out 4 statistical tests and when each is used
Spearman’s rho/rank
Chi-squared
Mann Whitney
Wilcoxon

5. What can exam questions ask?
May ask why do statistics
Likely to ask what p=0.05 means and significance level
Which test would be used and why
Questions can give you the calculated numbers and ask you to compare to the table and decide whether results significant
May link to hypothesis & which accepted
May link to type 1 or type 2 errors

6. Significance level (p value)
The concept of statistical significance is central to statistics.
A result that is statistically significant is unlikely to have occurred by chance.
we can never be 100% sure that chance has not played a part.
However, when the likelihood of obtained results having occurred by chance is slim, researchers will reject the null hypothesis and accept the alternative hypothesis.

7. P values
The p value most often used is the 5% level but could be 1%, 0.1% etc
the p value should be written as p 0.05 meaning that the probability that the results occurred due to chance are 5% or less.

8. Stats tests- how do they work?
Each test involves taking data collected in study and doing calculations which produce a single number called the test statistic.
In Spearman’s test, that test statistic is called rho, whereas for the Mann-Whitney test it is U.
This calculated value is often called the observed value (as based on observations made in the study)
To decide if the observed value is significant, this figure is compared to another number, found in a table of critical values; this is called the critical value

9. For some tests the observed value must be greater than the critical value and for other tests it must be less to reject NH!
It will tell you this at the bottom of the table of critical values but…
If test has the letter R in it then it must be gReateR e.g. speaRman, Chi-squaRed
If no R in name must be less – mann whitney & wilcoxon!

10. Which test to use? You need to consider 3 things:
whether a correlation or a difference between 2 groups
Whether independent or related groups of participants
Level of measurement (NOIR)

11. Level of measurement NOMINAL DATA
researcher identifies categories of behaviours and simply counts how many instances there are in each category
ORDINAL DATA
data capable of being placed into a rank order from highest to lowest but not about gaps between
INTERVAL AND RATIO DATA
more precise – they consist of data that are measured in fixed units with equal distances between all the points on the scale. Ratio data has true zero

12. Choosing a test

13. TYPE 1 AND 2 ERRORS Type I Error (false positive)
if we accept the alternative hypothesis when in fact the null was true.
Type II (2) error (false negative)
if we accept the null hypothesis when in fact the alternative hypothesis was true
Linked to p level
The stricter the significance level the more likely you are to miss a real pattern thus the more likely a type 2 error