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Kathy Foxall

Appendix: Statistical Methods  Stats are useful in the study of human behaviour  Help spot trends amid diversity  N=total number of observation or scores in a set  X= an observation or score  Sigma=Greek capital letter sigma, the sum of  Square root=the squre root of Organizing Data Constructing a Frequency Distribution  Frequency distribution o How often each possible score actually occurred  Grouped frequency distribution o Group adjacent scores into equal sized classes or intervals o E.g. range 1-50  (1-5, 6-10, 11-15) Graphing the Data  Bar graph/histogram o Draw rectangles above each score, indicating the number of times it occurred  Frequency polygon/line graph o Indicated by dot placed directly over score on horizontal axis, appropriate height on vertical axis  Graphs exaggerate or mask differences, depending on units Describing Data Measuring Central Tendency  Central Tendency o Characterize an entire set of data in terms of a single number o Mean  Sum of scores/number of scores o The Median  Sometimes extremely high score can dramatically raise the mean  Median more representative measure when extreme scores occur o Mode  Score that occurs most often Measuring Variability  Tell whether scores are clustered closely around the mean or widely scattered Range  Highest – Lowest scores Standard Deviation  Gives on average how much scores differ from the mean  Small standard deviation tells us most scores clustered near the mean, therefore mean is representative  Deviation Scores o Subtract mean from each score, add up all the numbers o Sum of scores will be zero o √∑(X-M)^2/N Transforming Scores  Working with scores that reveal where a person stands relative to others Percentile Scores  Gives the percentage of people who scored at or below a given raw score  You never do better than 100 percent of a group when you are a member of the group  However only rank people do not tell how far ap
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