descriptive statistics

• mean

  total of all values in a set of data divided by the number of values
• mean strengths

  makes use of all values and good for interval data
• mean limitations

  it is influenced by outliers (extreme scores) so it can be unrepresentative
• median

  arrange data from lowest to highest then find the central value
• median strengths

  not affected by extreme scores and good for ordinal data
• median limitations

  not as sensitive as mean and does not use all data
• mode

  the most frequently occurring value in a set of data
• mode strengths

  useful for nominal data (data in categories)
• mode limitations

  is not useful when there are several modes
• measures of dispersion - range

  minus the lowest score form the highest score
• measures of dispersion - range strengths 


  easy to calculate
• measures of dispersion - range limitations

  affected by extreme scores and does not use all of data
• measures of dispersion - standard deviation 


  looks at how far the scores deviate from the mean

  the square root of the variance calculates SD, a low SD means that more data is clustered close to the mean hence there is less data spread
• measures of dispersion - standard deviation strengths 


  precise measures where all data values are taken into account
• measures of dispersion - standard deviation limitations

  difficult to calculate and is affected by extreme values
• calculating percentages 


  can help the reader get a feel for the data at a glance

  if there are two conditions comparing the effects to see who most improved - number of participants who improved/ total number of participants x 100
• calculating percentage increase


  the difference in the two numbers must be calculated first, then divided by the original figure and times by 100
• calculating percentage decrease 


  the decrease between the two numbers being compared must be calculated then the decrease is divided by the original figure and multiplied by 100