Descriptive statistics

• Define correlational techniques

  Technique for analysing data

  Measures how strong a relationship is between two or more variables

  Requires quantitative data
• Define the 3 different types of correlation

  1)Positive correlation = as one variables increases the other increases

  2)Negative correlation = as one variables increases, the other decreases

  3)Zero correlation = occurs when a correlational study finds no relationship between variables.
• Define a correlation co-efficient, perfect positive correlation and a perfect negative correlation

  Correlation co-efficient = numerical measure of the strength and direction of the relationship between variables.

  
  

  Perfect positive correlation = has a correlation co-efficient of +1 (up, up - variables)

  
  

  Perfect negative correlation = has a correlation co-efficient of -1 (up, down - variables)

  
• Define a scattergram

  (Sometimes called a scattergraph) is a graph that shows the correlation between two sets of data (co-variables) by plotting points to represent each pair of scores.

  It indicates the degree and direction of the correlation between the co-variables

  
• State two strengths of correlational techniques

  1)Can be used when a lab experiment would be unethical as the variables are not manipulated, only correlated.

  2)Measures the strength of a relationship between variables, allowing for further research to be conducted.
• State two limitations of correlational techniques

  1)Not possible to establish a cause and effect relationship through conducting a correlation.

  2)Can only identify linear relationships, not curvilinear.
• Define a mean, give its strengths and limitations

  Mean = 'Average' - calculated by adding up all the scores in the data set and then dividing by the number of scores.

  (+) = Most representative of all the measures of central tendency because it is comprised of the whole data set.

  (-) = Can only be used with ordinal and interval data.
• Define a median, give its strengths and limitations

  Median = 'Middle Score' - calculated by putting all scores in rank order from smallest to largest then selecting the middle number from the data set.

  (+) = Not distorted by extreme scores

  (-) = Does not reflect all scores in the data set
• Define a mode, give its strengths and limitations

  Mode = 'most common' - calculated by identifying the most frequently occuring score within the data set.

  (+) = Not distorted by extreme scores.

  (+) = The only method which can be used within nominal data

  (-) = There can be more than one mode so it is not always a useful measure of central tendency.
• Define dispersion

  Are descriptive statistics that define the spread of data around a central value (mean or medium).

  There are two measures of dispersion: range and standard deviation
• Define range, give its strength and weaknesses

  Range = subtracting the lowest score in the data set from the highest score.

  (+) Easy to calculate mathematically without use of a calculator

  (-) Does not indicate the distribution pattern across the whole data set
• Define standard deviation, give its strengths and weaknesses


  How far the scores deviate from the mean e.g. if it is large = data is very dispersed around the mean (ppts scored very differently). If it is small = values are very concentrated around the mean (ppts scored very similarly)

  (+) Precise measurement of dispersion because all values in the data set are included in the calculation.

  (-) Extreme values can distort the measurement

  
• How to calculate percentages?

  Small number (on top) divided by big number (on bottom) overall x 100