Maths and Statistics

• Quantitative data

  Data in numbers.
• What is a strength of quantitative data?


  Easy to analyse, compare and summarise.
• What is a weakness of quantitative data?


  Oversimplifies human experiences and fails to tell us why a behaviour happens.
• Qualitative data


  Data in pictures or words, not numbers.
• What is a strength of qualitative data?


  Provides rich detail that can be used to explain human behaviour.
• What is a weakness of qualitative data?


  Difficult to summarise and analyse- may be difficult to draw conclusions from.
• Primary data


  Data that is collected by the researcher to be used in the current study.
• Secondary data


  Data that was collected for another puprose.
• What is a strength of primary data? 


  Data collection can be designed to fit the aims of the study.
• What is a weakness of primary data?


  Can be very time consuming and expensive way to collect data.
• What is a strength of secondary data?


  Simple, quick and cheap way to collect data.
• What is a weakness of secondary data?


  Data may not exactly for the needs of the study.
• Nominal data 


  Data which consists of names, labels or categories.
• Ordinal data


  Data can be ranked or ordered in some type of way.
• Interval data


  Data is measured using units of equal intervals.
• What is a strength of nominal data?


  Easy to generate from closed questions and large amounts of data can be collected quickly.
• What is a weakness of nominal data?


  Participants are not able to express degree of response and can only use the mode as a measure of central tendency.
• What is a strength of ordinal data?


  Indicates relative values on a linear scale and more informative than nominal data.
• What is a weakness of ordinal data?

  Gaps between ranks are not equal so a mean cannot be used to assess central tendency.
• What is a strength of interval data?


  More informative than nominal data and ordinal data as points are directly comparable and can used the mean as a measure of central tendency.
• What is a weakness of interval data?


  No absolute baseline to the scale so scoring zero may simply show that the scale does not accurately measure a participant’s behaviour.
• Mean


  The arithmetic average of a distribution, obtained by adding the scores and then dividing them by the number of scores.
• Mode


  The most frequently occurring score(s) in a distribution.
• Median


  The middle score in a distribution; half the scores are above it and half are below it.
• Median


  The middle score in a distribution; half the scores are above it and half are below it.The middle score in a distribution; half the scores are above it and half are below it.
• What is a strength of the mean?


  Uses all of the numbers in the data set and most valid representation.
• What is a strength of the mode?


  Unaffected by extreme scores.
• What is a strength of the median?


  Not affected by extreme scores so can be useful under such circumstances and it is easier to calculate.
• What is the weakness of the mean?


  There may be anomalous results which distort the results.
• What is the weakness of the mode?


  There may not be a mode, which suggests that this method lacks accuracy.
• What is the weakness of the median?


  Does not take into account every data value.
• Range


  The difference between the highest and lowest score in a distribution.
• Variance


  The square of standard deviation.
• Standard deviation


  A measure of how much scores can vary around the mean score.
• What is a strength of the range?


  Easier to calculate.
• What is a strength of variance/standard deviation?

  Precise measure of spread as all the data is spread.
• What is a weakness of the range?


  Fails to take into account the distributions of the numbeRS and its affected by the extreme numbers.
• What is a weakness of variance/standard deviation?


  May hide characteristics such as extreme values and harder to calculate than the range.
• Raw data


  Unprocessed data.
• Measures of central tendency 


  Averages.