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Lies, Damn Lies, and Statistics

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Title: Lies, Damn Lies, and Statistics


1
Lies, Damn Lies, and Statistics
  • An introduction to the mathematical concepts and
    operations used in testing and assessment

2
Fundamentals
  • Data collected from all members of a population
    are designated as population statistics. Such
    statistics are distinguished by the use of
    lower-case letters.
  • Statistics taken from a sample of members within
    a population are designated as sample statistics.
    Such statistics are distinguished by the use of
    upper-case letters.
  • All statistics are based on two concepts
  • Central Tendency
  • Variance

3
Central Tendency
  • There are three primary measures of central
    tendency mean, median and mode.
  • The mean, or arithmetic average, is the most used
    statistic and will be covered in the next slide.
  • The median is the middle number when all values
    are arranged in order, i.e. if we had 11 data
    points and arranged them from largest to
    smallest, the median would be the 6th number in
    the ranked order.
  • The mode is the number that appears the most
    frequently.

4
The mean (AKA arithmetic average)
  • Population (µ), sample

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8
We Need More Information!
  • The mean, though a popular and very useful piece
    of information, is rarely sufficient by itself to
    describe the data.
  • In order to put the mean into perspective, we
    need to know what the variance, or spread, in
    scores is. In order to do this the Standard
    Deviation was invented.

9
Describing Score Spread
  • Compute the mean of the individual scores

10
Describing Score Spread
  • Subtract the mean from each individual score to
    get the deviation score.

11
Describing Score Spread
  • Subtract the mean from each individual score to
    get the deviation score.
  • If the deviation scores sum to zero, you did it
    right. If they dont, check your math.

12
Describing Score Spread
  • Square each deviation score to get the squared
    deviation

13
Describing Score Spread
  • Square each deviation score to get the squared
    deviation
  • Add up the squared deviations to get the sum of
    squares.

14
Describing Score Spread
  • Compute the average of the squared deviations by
    dividing the sum of squares by n. This number is
    known as the variance (s2) .

15
Describing Score Spread
  • Since we had to square the deviations to avoid a
    zero average, we must now undo the squaring
    process by taking the square root of the
    variance. We have now successfully computed the
    standard deviation.

16
Standard Deviation
  • Population (s)

17
Standard Deviation
  • Sample (S)

18
Review of SD computation
  • Find the mean of the scores
  • Subtract the mean from each score (deviation
    score)
  • Square the deviation scores.
  • Sum the squared deviation scores and divide by n
    (pop) or n-1 (sample) to get the variance.
  • Take the square root of the variance.
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