L6 14/02

Question 1

Nominal definition

Answer 1

Discrete categories or groups e.g., gender, age etc

Question 2

Ordinal defintion

Answer 2

A pre-defined order e.g., very good, good, bad etc

Question 3

Interval defintion

Answer 3

Where the distance between measures is the same, and where zero is arbitrary, e.g., years, percentage change

Question 4

Ratio definition

Answer 4

Where the distance between measures is regular, but zero is absolute, e.g., a temperature scale

Question 5

Features of normal distribution

Answer 5

• A symmetrical distribution (a bell-shaped curve)
• Measures are concentrated round the mean
• Decrease in frequency at each tail of the curve
• Suitable for PARAMETRIC tests – normal distribution
• Sigma represents standard deviations

Question 6

Features of skewed distribution

Answer 6

• An asymmetrical distribution
• Positive (right) or negative (left) skew
• Positive is more common
• Suitable for NON-PARAMETRIC tests – skewed distribution

Question 7

What are the 2 reasons tests are compared?

Answer 7

• Compare means

- Correlate data to determine trends

Question 8

What are descriptive statistics used for?

Answer 8

Used to describe proportions

Question 9

What are inferential statistics used for?

Answer 9

Used to estimate the likelihood that the results of a study are due to chance alone or that the sample results represent a true reflection of the population of interest. They allow us to measure the strength of a relationship.

Question 10

What does statistical significance mean?

Answer 10

• A very specific term used to measure how confident we can be in the findings of research.
• Says that the results of your study are unlikely to have occurred by chance.

Question 11

P=0.5 means

Answer 11

There is a 50:50 probability of the effect being due to chance (NOT a good result for a study)

Question 12

P=0.05 means

Answer 12

There is a 1 in 20 probability (most studies use this for statistical significance)

Question 13

P=0.01 means

Answer 13

Highly significant

Question 14

What test would be most appropriate to compare the means of 2 normally distributed datasets?

Answer 14

T-test

Question 15

What assumption do “parametric” statistics tests make about the data?

Answer 15

It is normally distributed

Question 16

What does “statistical significance” mean about your results?

Answer 16

It is unlikely to have occurred due to chance

Question 17

What does a p-value of 0.05 usually mean?

Answer 17

Statistical significance

Question 18

What does a p-value of 0.01 usually mean?

Answer 18

Highly significant

Question 19

For a positive correlation, what will happen to a variable if the other variable DECREASES in magnitude?

Answer 19

It will also decrease

Question 20

What can “ANOVA” do that a “T-Test” cannot?

Answer 20

Compare 3 means

Question 21

What is true about the Wilcoxon Mann-Whitney U Test?

Answer 21

It is non-parametric

Question 22

P-value does not tell you what…

Answer 22

• It does not affect the strength of the effect:
• A highly significant result can be a tiny effect
• It just means that it probably does exist
• A high p-value does NOT mean that the effect does not exist; it just means you can’t prove it