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## Psych Stats Week 6

by: Hannah Wheeler

88

0

2

# Psych Stats Week 6 Psych 3301

Marketplace > University of Houston > Psych 3301 > Psych Stats Week 6
Hannah Wheeler
UH
GPA 3.0
Introduction to Psychological Statistics
Sonya Stokes

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How to calculate Raw Scores and Z Scores
COURSE
Introduction to Psychological Statistics
PROF.
Sonya Stokes
TYPE
Class Notes
PAGES
2
WORDS
KARMA
25 ?

## Popular in Department

This 2 page Class Notes was uploaded by Hannah Wheeler on Friday October 2, 2015. The Class Notes belongs to Psych 3301 at University of Houston taught by Sonya Stokes in Fall 2015. Since its upload, it has received 88 views.

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Date Created: 10/02/15
Psych Stats Week 6 The Normal Curve 0 As the sample size increases the shape of the distribution becomes more like the normal curve Standardization Z Scores and the Normal Curve Standardization Alows comparisons 2 distribution Comparing z scores 0 Transforming raw scores into 2 scores Step 1 Subtract the mean of the population from the raw score Step 2 Divide by the standard deviation of the population X u 039 0 Transforming z scores into raw scores Step 1 Multiply the z score by the standard deviation of the population Step 2 Add the mean of the population to this product Z Xz0u Usind Z Scores to Make Comparisons If you know your score on an exam and a friend s score on an exam you can convert to z scores to determine who did better and by how much 0 Z scores are standardized so they can be compared Transformind Z Scores lnto Percentiles Z scores tell you where a value ts into a normal distribution 0 Based on the normal distribution there are rules about where scores with a 2 value will fall and how it will relate to a percentile rank 0 You can use the area under the normal curve to calculate percentiles for any score The Central Limit Theorem 0 Distribution of sample Means is normally distributed even when the population from which it was drawn is not normal 0 Distribution of means ls less variable than a distribution of individual scores Distribution Of Means Mean of the distribution tends to be the mean of the population 0 Standard deviation of the distribution tends to be less than the standard deviation of the population 0 Standard error Standard deviation of the distribution of means

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