Distributions

• A normal distribution is an arrangement of data that is symmetrical and forms a bell-shaped pattern where the mean, median and/or mode fall in the centre at the highest peak.
• In a normal distribution most data will form around the mean/ average.
• The mean score is the average, calculated by adding up the total and dividing by the number of scores.
• The standard deviation is how far the scores are spread from the mean (larger s.d means more variation in the scores/ wider spread).
• A skewed distribution is one where frequency data is not spread evenly (i.e. normally distributed), the data is usually clustered at one end.
• On a graph data that is positively skewed has a long tail that extends to the right.
• On a graph data that is negatively skewed will have a long tail that extends to the left.
• Typically when data is skewed to the right (positively skewed), the mean will be greater than the median (middle number when in order) and when data is skewed to the left (negatively skewed), the median will typically be greater than the mean.
• Skewness affects the relationship between the mean and the median in a distribution by pulling the mean towards the direction of the skew.
• The positions of the mean, median and mode determine the type of distribution.