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TheNormalDistribution

# 0 std dev 1 raw scores below mean have mean z scores

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Unformatted text preview: v. = 1 Raw Scores below mean have mean (-) z-scores (-) Raw scores above Raw mean have (+) z-scores Z-scores Z-scores Benefits of using z-scores: Can compare standardized scores when Can original units of measurement differ original Estimate probabilities/proportions Calculate percentile ranks Look for outliers in data for a variable Rule of thumb: + 3 standard deviation units Rule Z-Score Formula & Example Z-Score If a variable has M = 100 and SD = 50, If the z-score for a raw score of 200 is: z-score 200 is: X − μ 200 − 100 Z= = = 2.0 σ 50 Interpretation: The raw score is two SDs Interpretation: (2 increments of 50) above the mean. (2 Finding Normal Probabilities Finding Probability is the Probability is measured area under the curve! under...
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