Data, Graphs and statistics

• raw data- data that is unprocessed (no in graphs)
• Levels of data measurement- Nominal, ordinal and interval
• Nominal data - data that is categorised or "nominated" eg. hair colour or shoe size.
• Nominal data strength- easy to classify.

  Weakness- Too simplified- can only say if something is similar or dissimilar
• Ordinal data- Numerical data which can be placed in an order. Subjective but direct comparisons can be made.
• Interval data - Numerical, uses a pre-existing data set or scale (eg. g , kg).

  strength- allows for dividing and multiplication - specific comparisons.

  Weakness- specialist equipment (usually ruler or stopwatch)
• Measures of central tendency- Mean, mode and median
• Mean - most representative, but not good for nominal or ordinal data and is affected by extreme data
• • Mode- appears the mostused with any type of data, easy to determine, but is unhelpful in small sets of data
• Median- middle score- unaffected by extreme values as it ignores outliers, but is not useful for nominal data
• Range - difference between highest and lowest value. - Easy to calc, but is affected by extremes.
• Dispersion- how spread out the data is
• SD- calculates the distance from the mean of the group

  Strength- precise; accounts for all data

  Weak- diff to calc.
• Higher SD- Data more spread.