Lecture 7_z-scores

Lecture 7_z-scores - 9/13/2010 z-scores 1 Raw Scores Data...

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9/13/2010 1 z- scores 1 Raw Scores • Data are often expressed as raw scores, where subject responses are not transformed from the original data collection – e.g., total number of points earned on a test, number of answers right on a quiz, score on a depression or other personality inventory 2 Raw Scores • Raw scores provide no information about the position of a score relative to others – e.g., suppose that you got a score of 89 out of 100 on the first exam; your score provides no information on how you did relative to your classmates--- or to a larger population 3
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9/13/2010 2 Standardized Scores • Standardized scores give the exact location of a score in a distribution of scores, indicating how far a score is from the average (i.e., its distance from the mean) in standard deviation units. – Often used with norm-referenced assessments where it of interest to know how individuals score in reference to their peers, or a larger population 4 Standardized Scores • Allow comparison of raw scores • Determine where a person's score falls in comparison to another person or a group • Used to compare individuals to their peers or to a larger population 5 Examples of Standardized Scores – IQ scores : ( = 100, = 15) • An IQ score of 102 does not mean that 102 questions were answered correctly; it means that the person is slightly above avg. 6
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9/13/2010 3 Examples of Standardized Scores – SAT scores : ( = 500, = 100) • An SAT score of 800 on a given subscale (such as verbal, analytical, or quantitative) means that you scored 3 standard deviation units above the mean… thus you are well above the average on the test 7 Percentiles • Percentiles are often used to help interpret
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Lecture 7_z-scores - 9/13/2010 z-scores 1 Raw Scores Data...

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