Analyzing Data

Question 1

What is nominal data?

Answer 1

a frequency count for distinct categories where something can only belong to one category (e.g. number of people who pass or fail a driving test)

Question 2

What is Ordinal data?

Answer 2

This is where numbers can be placed in ascending or descending rank order (e.g. on a rating scale where 1=attractive and 10= unattractive)

Question 3

What is Interval data?

Answer 3

measurements are taken from a scale where each unit is the same size and the gap between each unit is fixed and equal (e.g. the difference between a temperature of 100 and 90 is the same difference as between 90 and 80) (scoring data)

Question 4

What are the strengths of nominal data?

Answer 4

easy to generate and large amounts of data can be categorized quickly

Question 5

What are the weaknesses of nominal data?

Answer 5

because it doesn’t not give a numerical score for each P, this crude type of data does not permit sensitive analysis

Question 6

What are the strengths of ordinal data?

Answer 6

more detailed than nominal so provides more information

Question 7

What are the weaknesses of ordinal data?

Answer 7

Gaps between the values aren’t equal so a mean cannot be used to assess central tendency

Question 8

What are the strengths of interval data?

Answer 8

open to most types of statistical analysis. For example, you could consider all types of central tendencies as well as both the range and standard deviaton

Question 9

What are the weaknesses of interval data?

Answer 9

In interval scales that do not contain scientific measurements there is no absolute baseline to the scale so scoring 0 may not mean the participant doesn’t demonstrate the variable but that the scale doesn’t measure it.

Question 10

What are the two tests of differences?

Answer 10

independent measures
repeated measures (also matched pairs)

Question 11

What is the test of relationship?

Answer 11

correlational design?

Question 12

What are the 3 stats tests for independent measures?

Answer 12

nominal - Chi square
ordinal - Man Whitney
interval - Unrelated T test

Question 13

What are the 3 stats tests for repeated measures (and MP)

Answer 13

nominal - sign test
ordinal - wilcoxon test
interval - related T test

Question 14

What are the 3 stats tests for correlational designs?

Answer 14

nominal - chi squared (x2)
ordinal - spearman’s rho
interval - pearson’s r

Question 15

What is the minimum level of significance acceptable in psychology?

Answer 15

0.05 (5%) meaning we are 95% certain that our results are not due to chance

Question 16

What is a type 1 error (false positive)?

Answer 16

where we wrongfully accept the experimental hypothesis (conclude results are significant when they’re not).

This means we believe there is a difference or relationship, when actually no such relationship exists

Question 17

What is a type 2 error (false negative)?

Answer 17

where we wrongfully accept the null hypothesis (conclude our results are not significant when they are)

This means we believe there is no difference between conditions or no relationship when infact a relationship does exist.