Data

• Nominal data- participants fall into categories (counting/frequencies)
• ordinal data- data can be organised from highest to lowest (places in a race)
• interval data- data that does not have a fixed zero point (temp)
• strengths of nominal data- easy to generate from closed questions, large amount of data collected quickly, increasing reliability
• weaknesses of nominal data- without linear scale ppts may be unable to express degrees of response, only use mode as measure of spread of data
• strengths of ordinal data- indicates relative values on a linear scale instead of totals, more info than nominal data
• weaknesses if nominal data- gaps between values aren't equal so cant use mean to asses central tendency
• strengths of interval level data-more info as points directly comparable as are all of equal value, scientific measures used to record distance between values, highly reliable
• weaknesses of interval level data- no absolute baseline if scientific methods not used, ppts can demonstrate a variable that scale doesnt measure