PSYC 1010 Study Guide - Final Guide: Central Limit Theorem, Standard Deviation, Normal Distribution
29 Jun 2018
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1010 exam Chapter 6
•Normal curve: bell-shaped curse, symmetric
Standardization, z score and the normal curve
•Standardization: way to convert individual scores form different normal distribution to a
shared normal distribution with a know mean, standard deviation and percentiles
•We can standardize difference variables by suing their means and standard deviation to
convey any raw score into a z score,
•z score: the number of standard deviation a particular score is from the mean
The central limit theorem
•Refers to how a distribution of sample means is a more normal distribution the a distribution
of score, even when the population distribution is not normal
•Distribution of means: composed of many means that are calculated from all possible
samples of a given size, all taken from the same population
Characteristics of the Distribution of means
•Distribution of means needs its own standard deviation
•Standard error: name for the standard deviation of a distribution of means
•Formula;
•3 important characteristics of the distribution of means;
•size increases but mean of a distribution of means remains the same
•standard error is smaller then the standard deviation of a distribution score. sample size
increase, error decreases
•normal curve
Using The Central Limit Theorem to Make Comparisons with Z Score
•Z formula changes to,
•Have to use standard error formula to find the bottom number
•Z statistic, we can determine how extreme the mean number of hospitalization is in terms of
a percentage
