Psy 202- Chapter 4
Psy 202- Chapter 4 Psy 202
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This 4 page Class Notes was uploaded by T'Keyah Jones on Wednesday September 7, 2016. The Class Notes belongs to Psy 202 at University of Mississippi taught by Dr. Melinda Redding in Fall 2016. Since its upload, it has received 6 views. For similar materials see Elementary Statistics in Psychology (PSYC) at University of Mississippi.
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Date Created: 09/07/16
Psychology 202 September 6, 2016 Chapter 4: Standard Scores, the Normal Distribution and Probability a. Standard scores Raw score expressed in terms of how many standard deviations it is from the mean Commonly called “z-scores” z-scores Directly corresponds with standard deviation Basic standard score Represented with a lowercase/uppercase Referred to as standard normal distribution Has a mean of 0 and standard deviation of 1 Positive above the mean Negative below the mean Rare to get a score of 2-4 standard deviation above the mean Formula: z= X-µ z= X-M s advantage 1. z-scores tell us how far above or below the mean of given score falls 2. z-scores allows us to make comparisons across different distributions 3. z-scores allow us to estimate the probability of an event occurring -4 -3 -2 -1 0 1 2 3 4 BELOW MEAN ABOVE MEAN Example Wechsler I.Q. scores have a mean of 100 and a standard deviation of 15 Wechsler-R score of 144 (µ=100, =15) compared to Stanford Binet L- M score of 145 (µ=100, =16) W: z= X - µ = 144-100 = 2.93 15 S: z= X - µ = 145-100 = 2.81 16 b. Probability How likely it is that an event or outcome will occur Number of ways a specific outcome (or set of outcomes) can occur, divided by the total number of possible outcomes Always between 0 and 1 (always positive) P Proportion p Probability To find Probability Use the normal distribution and z-scores Look for whether the outcome is “common” or “rare” Rare < .05 c. Normal Distribution Unimodal and symmetrical Frequencies decrease as the curve moves away from midpoint Regions under the normal curve contain a specific percentage of scores d. Appendix A: Table 1 Allows us to determine specific proportions (percentages) of cases under specific areas of the normal curve Table provided in the book and on Blackboard Print this table out for class on Thursday -On Blackboard: Content, z-table Use Column B 0 1.00 z= 0.55 Use Column C 0 1.00 z= 0.55 Use Column A 0 1.00 z=0.55 e. Percentile Ranks Tells the percentage of cases whose scores are at or below a given level in a frequency distribution Can be a little deceiving Thethean (0) 50 percentile Scores above the mean Greater than 50 percentile Scores below the mean th Lesser than 50 percentile We can use the z-table to find the percentile below a given score and use it to find the z-scores when given a percentile mark. Formula: z = X - µ X= z () +µ Example 84 percentile Above mean z-score: +1.00 µ= 100 = 15 a) A z-score of -2.00 2.28% -2.00 0 b) A z-score of -1.00 15.87% -1.00 0
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