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

Levels of data Nominal Ordinal Interval Ratio

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.

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

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

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

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.

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

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’

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

Types of data Qualitative Quantitative

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

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

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

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

Homework: RM Workbook page 19