descriptive statistics

• measures of central tendency


  results generated from research are raw data that needs summarising by working out measure of central tendency

  mean - adding up all scores in data set and dividing by total number of scores - only measure that includes all data

  median - middle score - putting scores in order and finding middle

  mode - most common score within data set - can be bi-modal (two modes) or no mode if all scores are different - mode can sometimes be only data that can be used like data in categories
• measures of central tendency evaluation

  mean: advantage - sensitive measure (uses all scores) - disadvantage - skewed my extreme scores

  median: advantage - not skewed by extreme scores - disadvantage - not a sensitive measure

  mode: advantage - not skewed by extreme scores - disadvantage - not a sensitive measure
• measures of dispersion


  tells us how spread out the scores are using the range and standard deviation

  range - simplest calculation - subtracting lowest score from highest - large range = large spread, small range = small spread

  standard deviation (SD) - takes all scores in data set into account - large SD = large spread, small SD = small spread - uses all scores and shows average deviation of these scores from mean - small SD shows scores closely clustered around mean and large SD widely spread out from mean
• measures of dispersion evaluation

  Range: advantage - easy to calculate - disadvantage - not a sensitive measure

  standard deviation: advantage - sensitive measures - disadvantage - difficult to calculate (uses all scores)