Statistics Flashcards
What is Interval data?
Data measured in fixed units with equal distance between points on the scale
For example: temperature measured in centigrade
What is ordinal data?
number score, but the number represents rank position
Example: 1st, 2nd, 3rd, etc. The positions of football teams in a league are examples of ordinal data
What is nominal data?
Puts sample into categories, categories them into groups
Example: using “tally marks” to record the number of people in one group or another
What is skewed distribution?
Where frequency data is not spread evenly, the data is clustered at one end. Data that is positively skewed has a long tail that extends to the right
What does standard deviation find?
Shows the spread of scores from the mean. The greater the standard deviation the greater the spread of scores from the mean.
When would you use Mann-Whitney U?
- Test of difference
- Ordinal data
- Independent group design
When would you use Willcoxen?
- Test of difference
- Ordinal data
- Matched pairs/repeated measures
When would you use Spearman’s rank?
- Test of correlation
- Ordinal data
When would you use Chi squared?
- Test of difference
- Nominal data
- Independent group design
What is a type 1 error?
False-posative, if an investigator rejects a null hypothesis that is actually true in the population
What is a type 2 error?
False-negative, if the investigator fails to reject a null hypothesis that is actually false in the population
What do you need to remember when doing standard deviation?
- Deduct the mean from each score in set
What do you need to remember when doing Mann-Whitney U?
- Rank separately
- na is the total number of scores you have in Condition A
- nb is the number of scores in Condition B
What do you need to remember when doing Wilcoxen?
- Rank together
- Ignore 0
- Add up posative ranks
- Add up negative ranks
- T is the smallest out of the 2
- N is the number of scores
What do you need to remember when doing Spearman’s rank?
- Rank separately
- Find difference between condition 1 rank and condition 2 rank
- n = number of participants
- positive = positive correlation
- negative = negative correlation
(The closer it is to 0 , the weaker the correlation, The closer it is to 1, the stronger the correlation)