Introduction to Statistics

Question 1

Why are statistics important? (6)

Answer 1

To make informed decisions
To establish cause and effect
To predict what is likely in the future
Credibility
To test effectiveness of interventions
To improve quality if assessment procedures, treatment procedures and services.

Question 2

3 Categories of Statistics

Answer 2

• Descriptive (organising, summarising and describing data)
• Correlational (relationships)
• Inferential (generalising) - significance

Question 3

Variable

Answer 3

Logical attribute or a set of attributes of a thing, a place or a person. weight, gender, race, HR, temperature, mood.
If you assign a nr to it, it becomes data.

Question 4

Independent vs dependent variables

Answer 4

Independent: Variable that is presumed to influence the other variable.
Dependent: Variable affected by the independent variable.

Question 5

Types of Quantitative Variables (2)

Answer 5

Discrete variables
Continuous variables

Question 6

Discrete Variables

Answer 6

Counted
Non decimal (0,1,2,3…)
May have derived units of measurement (Beats per minute)
Interval or ratio
Example:
Nr of bones in the body
Nr of muscles attached to a joint
Nr of repetitions of muscle contractions

Question 7

Continuous Variables

Answer 7

Measured
Decimal (0.0, 0.5, 1.0…)
Unit of measurement: yes e.g. cm, °C, mmgh.
Interval or ratio
Examples:
Height
Temperature
Blood pressure
Force of muscle contraction

Question 8

Scales of measurement - Qualitative vs Quantitative Data

Answer 8

Qualitative: Nominal or ordinal
Quantitative: Interval or Ratio (either discrete or continuous)
Ordinal scales can sometimes be quantitative, but most often are qualitative.

Question 9

Criteria for Classification of Scales of Measurement

Answer 9

1. Can the variable be measured or counted?
2. Are observations in the variable in rank or size order?
3. Are observations in the variable separated by equal distance or size?
4. Does the variable have a meaningful zero value?

Question 10

Nominal Scale

Answer 10

Does not fulfill any of the criteria.
Names to identify or categorize.
No order, no magnitude, no comparison.
Examples: Gender, climate (polar, temperate, tropical, desert), nationality, sexual orientation.

Question 11

Ordinal Scale

Answer 11

Always has rank or size order
Might be counted or measured
Might have meaningful zero value
Never has equal distance between categories
MRC scale and modified Ashworth scale, 1st place, 2nd place, 3rd place, educational qualifications (bachelor, masters, doctorate), time of day (night, dawn, noon, afternoon, evening).
Used to arrange data into series or order of occurrence.

Question 12

Interval Scale

Answer 12

Either counted or measured
Have rank or size order
Have equal distance between categories
Do NOT have meaningful zero value
There is a clear relationship between observations, and they have a common unit of measurement.
Time of day on a 12h clock, IQ score (40-160), temperature in Celsius and Fahrenheit, BMI, Numeric pain rating scale (don’t know the distance between categories).

Question 13

Ratio Scale

Answer 13

Either counted or measured
Has rank or size order
Has equal distances between categories
Has a meaningful zero value
HR, weight kg, force (N) (not vectors), money in your wallet, Visual analogue scale (research has found the distance between categories).