Week 10

• Summary measure that attempts to describe a whole set of data with a single value that represents the middle of centre of its distribution

• Sum of the value of each observation in a data divided by the number of observations

Observations that are distant or distinct from the other observations in a dataset

• The middle value in a distribution when values area arranged in ascending order • Divides data in half

• The most commonly occurring value in a distribution

• Measure of the asymmetry of a distribution

• Positive skew, more data on the left side - Negative skew, more data on the right side

• When scores either side are very close together - Resulting in sharp thin bell curve

• Flat wide bell curve - Data are far either side

-1 and +1

• Measures of spread of the data around the mean - Standard deviation is a measure of the average deviation of the scores from the mean

An interval of values computed from the sample, that is almost sure to cover the true population - Confidence intervals tell you the limits within which the population mean is likely to fall

• Standardization or putting scores/ values into a form that you can use to compare across tests. These scores become known as ‘standardized’ scores • Transform raw scores into Standardised scores • Tells you how many standard deviations above or below the mean a score is

Mesokurtic: Distributions that are moderate in breadth and curves with a medium peaked height.

leptokurtic, mesokurtic, platykurtic

the sharpness of the peak of a frequency-distribution curve.