1. 1.3 Data Recording, Analysis and Presentation
Levels of data – nominal, ordinal, interval and ratio
Types of data – qualitative, quantitative, primary and secondary

2. Levels of data
Nominal
Ordinal
Interval
Ratio

3. Nominal Data
Used for labelling variables without any quantitative value
Nominal scales would simply be called “labels”
Nominal Data is data which cannot be assigned a numerical value of any true mathematical significance
Example: Jerrsey numbers in basketball are measures at the nominal level. A player with number 30 is not more of anything than a player with number 15, and is certainly not twice whatever number 15 is.

4. Nominal Data
Notice in the example, all scales are mutually exclusive (no overlap) and none have a numerical significant
Nominal = name

5. Ordinal Ordinal = Order of the values which is important
However, the differences between each is not known
We don’t know and cannot quantify how much better happy is from OK. We also cant say the difference between very unsatisfied is the same as between somewhat unsatisfied

6. Interval
Numeric scales in which we know the order and the exact differences between the values
Example: Celsius temperature – intervals between 50 and 60 degrees is 10 degrees. This is the same difference between 10 and 20 degrees.
Interval = space inbetween

7. Interval data
However, interval scales have no “true zero” eg. there no such thing as ‘no temperature’
Without a ‘true zero’ it is impossiple to compute ratios.
You can add with interval data… 10 degrees + 10 degrees = 20 degrees
You cannot multiple or divide with interval data… 20 degrees is not twice as hot as 10 degrees. A size 16 is not twice as big as a size 8 in clothing.

8. Ratio
Tells us about the order, the exact value between units and they have an absolute zero which allows for a wide range of both descriptive and inferential statistics to be applied
Example; height and weight

9. Nominal = name, label a series of values
Ordinal = order of choices
Interval = order of values and quantify the difference
Ratio = ultimate-order, interval values plus ‘true zero’

11. Using a QR scanner, watch the video and add any additional information to the four boxes with explanations of each type of data
Identify which image correlates with each data type
Identify what type of data each example illustrates
Answer the bottom box on your A3
Ask for the Survey handout and identify which type of data each question asks for

12. Types of data
Qualitative
Quantitative

13. Split class into two groups
Group 1: qualitative
Group 2: quantitative
You should split again into pairs. You must write notes fully explaning what your type of data is. You should provide an example or two. You are then expected to teach this to another pair who is learning the opposite type of data
Once you have done this, you should stay in your pairs and evaluate each type of data using the handout provided

14. Task 1 – Qualitative data
Take each evaluation point and extend fully using example where possible. You get 1 mark for every evaluative point that you have elaborated. Remember when elaborating you could give examples, relate to the effect these strengths and weaknesses may have on the results, etc.
Strengths
Depth detail insight
Context and so more valid
Meanings and motives
Does not pigeon hole people
Less open to bias in that you don’t look for information to back up aims you already have
Can get new info with open questions
Weaknesses
Unwieldy
Behaviour and interviews open to interpretation
Not usually reliable
Unrepresentative

15. Task 2 – Quantitative data
Take each evaluation point and extend fully using example where possible. You get 1 mark for every evaluative point that you have elaborated. Remember when elaborating you could give examples, relate to the effect these strengths and weaknesses may have on the results, etc.
Strengths
Can look for cause and effect
You can make comparisons see patterns and trends
Easy to analyse
Can repeat to test reliability
Large sample / generalisable
Weaknesses
Distort the truth
Lacks validity Pigeon holes doesn’t give scope for full answer
Does not give context i.e. meanings lack depth and detail
Easy to be bias you are likely to find what you are looking for and statistics from another source may have a deliberate bias

16. Types of data Primary Secondary
In the same groups as before, one half select primary data, the other; secondary data
You are expected to write an explanation of what the type of data is, provide an example as well as outline strengths and weaknesses of each

18. Homework:
RM Workbook page 19