Ch08+Lecture

# Ch08+Lecture - CHAPTER 8 Hypothesis Testing with z Tests:...

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CHAPTER 8 Hypothesis Testing with z Tests: Making Meaningful Comparisons

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The Versatile z Table: Raw Scores, z Scores, and Percentages Benefits of standardization: allowing fair comparisons z table: provides percentage of scores between the mean and a given z score
See Appendix B.1

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Figure 8-1: The z Distribution We can use a  z  table to determine the percentages below and above a particular  z score. For example, 34% of scores fall between the mean and a  z  score of 1.
Figure 8-2: Calculating the Percentile for a Positive z Score of z = +0.98 Drawing curves helps us to determine the appropriate percentage. For a positive  z  score, add 50%  to the percentage between the mean and that  z  score to get the total percentage below that  z   score, the percentile. Here, we add 50% below the mean to the 33.65% between the mean and a  z   score of 0.98 to calculate the percentile, 83.65%

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Figure 8-3: Calculating the Percentage Above a Positive z Score of z = +0.98 For a positive z score, we subtract the percentage between the mean and that z score from the 50% (the total percentage above the mean) to get the percentage above that z score. Here we subtract the 33.65% between the mean and the z score of 0.98 from 50%, which yields 16.35%.
Figure 8-4: Calculating the Percentage at Least as Extreme as Our z Score of 0.98 For a positive z score, we double the percentage above that z score to get the  percentage of scores that are at least as extreme—that is, at least as far from the mean —as our z score is. Here, we double 16.35% to calculate the percentage at least this  extreme: 32.70%.

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Figure 8-5: Calculating the Percentile for a Negative z Score of -1.82. As with positive
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## This note was uploaded on 09/30/2011 for the course PSY 3301 taught by Professor Staff during the Spring '08 term at Texas State.

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Ch08+Lecture - CHAPTER 8 Hypothesis Testing with z Tests:...

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