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Mean, Median, Mode
Chapter 3
 Central tendency
  • A statistical measure
  • A single number to define the center of a
    set of scores
 Purpose
  • Find the single number that is most typical or best
    represents the entire group
 Estimate a population
  • The central tendency (average) of a sample is
    sometimes used to estimate the entire population
 Mode – most common
  value in the data
 Median – middle case
  (data point) in the data
 Mean – balance point of
  all the data

 Choose based on scale
  (level) of measurement
  and skewness
Used with interval or ratio data, except when the
distribution is skewed or indeterminate
 The mean: sum of all the scores divided by the number of
  scores in the data
 Symbols: Greek μ for population, M for sample
 Some texts and publications use X but we will not use it in
  this course.

       Population Mean          Sample Mean

                  X                         X
                                  M
                 N                      n
 The balance point for a distribution of
  scores, equal weight on either side.
 Compute Σf = n
 Compute f · X for each value in the data set
 Compute             Value (X)      f         fX
                          10         1       10
  ΣX = Σ(f · X)            9         2       18
 M = ΣX / n               8         4       32
                          7               0        0
                          6               1        6
                              Total n = Σf = 8   ΣfX = 66

                           M = ΣX / n = 66/8 = 8.25
1. Determine the combined sum of all the scores
   ΣX1 + ΣX2 = ΣXcombined
2. Determine the combined number of scores
   n1 + n2 = ncombined
3. Compute new mean
   Mcombined = ΣXcombined /ncombined


                              X1    X2
        overall mean M
                              n1 n2
 Changing the value of one score always
  changes the mean.
 Introducing a new score or removing a score
  usually changes the mean (unless the score is
  exactly equal to the mean).
 Adding or subtracting a constant from each
  score changes the mean by the same constant.
 Multiplying or dividing each score by a
  constant multiplies or divides the mean by
  that constant.
Used with ordinal data.
Used with skewed interval or ratio data
 The median is the midpoint of
  the scores in a distribution
  when they are listed in order
  from smallest to largest.

 The median divides the scores
  into two groups of equal size.

 If the data have an even
  number of scores, median is
  the midpoint between two
  scores.
 Mean is the balance point of a distribution
  • Defined by distance from center (“weight”)
  • Not necessarily the midpoint
 Median is the midpoint of a distribution
  • Defined by number of scores
  • Usually is not the balance point
 Both measure central tendency, using two
  different concepts of “middle”
Used with nominal data
Often reported as percentage, not category
 The mode is the score or category that has
  the greatest frequency of any in the
  frequency distribution.
  • Can be used with any scale of measurement
  • Corresponds to an actual score in the data
 It is possible to have more than one mode
The extreme values affect the Mean more than
they affect the Median
 In positively skewed data (a) Mean is larger than Median
 In negatively skewed data (b) Mean is less than Median
 When you do not have a graph of a distribution, comparing the
  Mean and the Median tells you if there is skew present.
 Mean, influenced by extreme scores, is pulled
  toward the long tail a lot (positive or negative)
 Median, in order to divide scores in half is less
  affected by the extreme scores
 Mode is not affected by extreme scores
 If Mean – Median > O, the distribution is
  positively skewed.
 If Mean – Median < O, the distribution is
  negatively skewed
Measure of         Appropriate to choose when … Should not be used when…
Central Tendency
Mean               •No situation precludes it   •Extreme scores
                   •First choice measure of     •Skewed distribution
                    central tendency            •Ordinal scale
                                                •Nominal scale
Median             •Extreme scores              •Nominal scale
                   •Skewed distribution
                   •Ordinal scale
Mode               •Nominal scales              •Interval or ratio data, except
                   •Discrete variables          to accompany mean or median
                   •Describing shape of
                   distribution
Core concept for rest of statistics.
The mean will reappear all semester.

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Central Tendency - Overview

  • 2.  Central tendency • A statistical measure • A single number to define the center of a set of scores  Purpose • Find the single number that is most typical or best represents the entire group  Estimate a population • The central tendency (average) of a sample is sometimes used to estimate the entire population
  • 3.  Mode – most common value in the data  Median – middle case (data point) in the data  Mean – balance point of all the data  Choose based on scale (level) of measurement and skewness
  • 4. Used with interval or ratio data, except when the distribution is skewed or indeterminate
  • 5.  The mean: sum of all the scores divided by the number of scores in the data  Symbols: Greek μ for population, M for sample  Some texts and publications use X but we will not use it in this course. Population Mean Sample Mean X X M N n
  • 6.  The balance point for a distribution of scores, equal weight on either side.
  • 7.  Compute Σf = n  Compute f · X for each value in the data set  Compute Value (X) f fX 10 1 10 ΣX = Σ(f · X) 9 2 18  M = ΣX / n 8 4 32 7 0 0 6 1 6 Total n = Σf = 8 ΣfX = 66 M = ΣX / n = 66/8 = 8.25
  • 8. 1. Determine the combined sum of all the scores ΣX1 + ΣX2 = ΣXcombined 2. Determine the combined number of scores n1 + n2 = ncombined 3. Compute new mean Mcombined = ΣXcombined /ncombined X1 X2 overall mean M n1 n2
  • 9.  Changing the value of one score always changes the mean.  Introducing a new score or removing a score usually changes the mean (unless the score is exactly equal to the mean).  Adding or subtracting a constant from each score changes the mean by the same constant.  Multiplying or dividing each score by a constant multiplies or divides the mean by that constant.
  • 10. Used with ordinal data. Used with skewed interval or ratio data
  • 11.  The median is the midpoint of the scores in a distribution when they are listed in order from smallest to largest.  The median divides the scores into two groups of equal size.  If the data have an even number of scores, median is the midpoint between two scores.
  • 12.  Mean is the balance point of a distribution • Defined by distance from center (“weight”) • Not necessarily the midpoint  Median is the midpoint of a distribution • Defined by number of scores • Usually is not the balance point  Both measure central tendency, using two different concepts of “middle”
  • 13. Used with nominal data Often reported as percentage, not category
  • 14.  The mode is the score or category that has the greatest frequency of any in the frequency distribution. • Can be used with any scale of measurement • Corresponds to an actual score in the data  It is possible to have more than one mode
  • 15. The extreme values affect the Mean more than they affect the Median
  • 16.  In positively skewed data (a) Mean is larger than Median  In negatively skewed data (b) Mean is less than Median  When you do not have a graph of a distribution, comparing the Mean and the Median tells you if there is skew present.
  • 17.  Mean, influenced by extreme scores, is pulled toward the long tail a lot (positive or negative)  Median, in order to divide scores in half is less affected by the extreme scores  Mode is not affected by extreme scores  If Mean – Median > O, the distribution is positively skewed.  If Mean – Median < O, the distribution is negatively skewed
  • 18. Measure of Appropriate to choose when … Should not be used when… Central Tendency Mean •No situation precludes it •Extreme scores •First choice measure of •Skewed distribution central tendency •Ordinal scale •Nominal scale Median •Extreme scores •Nominal scale •Skewed distribution •Ordinal scale Mode •Nominal scales •Interval or ratio data, except •Discrete variables to accompany mean or median •Describing shape of distribution
  • 19.
  • 20.
  • 21. Core concept for rest of statistics. The mean will reappear all semester.