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Part%209%20Research%20Strategies%20and%20Validity0

# Lessaffectedthanthemeanbydistortingeffectsofoutliners

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Unformatted text preview: to the population of interest? – Statistical significance Examples of descriptive statistics Examples of descriptive statistics • Measures of central tendency – Mean, median, mode • Measures of dispersion – Variance, standard deviation, range • Measures of relationship – Pearson’s product moment correlation coefficient Measures of central tendency: Measures of central tendency: Mode & Median • Mode – Which is the most common? – Applicable to data measured on any scales (nominal, etc) • Not commonly used 30 30000 25 Num ber of indiv iduals Number of v otes 25000 20000 15000 10000 20 15 10 5 5000 0 0 NDP LIB CON GRN MP IND COM CAP ML Political party 60 70 80 90 100 110 120 130 140 IQ score • Median – Which one is in the middle? • Less affected than the mean by distorting effects of outliners Tricky to calculate, requiring all values to be placed in order Measures of central tendency: Measures of central tendency: Mean • Advantages – Easily understood and computed • Otherwise known as the ‘average’ – Useful in inferential statistics • Disadvantages – Subject to distorting effects of outliers – Cannot be applied to nominal or ordinal scale data • It must be meaningful to add different values together ∑X M= n Measures of central tendency: Measures of central tendency: Mean Sigma: “add together all subsequent values” M= M: “mean value of all X’s” “insert numbers here” X ∑ n “number...
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