PSY1022 Chapter Notes - Chapter Prescribed: Sampling Distribution, Central Limit Theorem, Statistical Parameter
26 May 2018
School
Department
Course
Professor
PSY1022 - readings - week 12 - drawing conclusions from inferential statistics
- probability is used to predict the type of samples are likely to be obtained from
a population
- use z-score to describe the relative standing of an entire sample - by computing
a z-score for the sample’s mean
- sampling distributions of means
• a frequency distribution showing all possible means that occur when
samples of a particular size are drawn from a population
• central limit theorem
•
o a statistical principle that defines the shape, the mean, and the
standard deviation of a sampling distribution
- standard error of the mean
• the standard deviation of the sampling distribution of means
- finding the probability of sample means
• use a sampling distribution of means
•
o a sampling distribution is the frequency distribution of all possible
sample means
- sampling error
• when random chance produces an unrepresentative sample from a
population, with the result that the sample’s statistic is different from the
population parameter it represents
- region of rejection
• the part of a sampling distribution containing means that are so unlikely
that we reject that they represent the underlying raw score population
• the extreme tails of a sampling distribution containing those sample
means considered unlikely to be representing the underlying raw score
population
- criterion
• the probability that defines whether a sample is unlikely to represent the
underlying raw score population
- critical value
• the score that marks the inner edge of the region of rejection in a
sampling distribution; values that fall beyond it lie in the region of
rejection
•
find more resources at oneclass.com
find more resources at oneclass.com
Document Summary
Psy1022 - readings - week 12 - drawing conclusions from inferential statistics. Probability is used to predict the type of samples are likely to be obtained from a population. Use z-score to describe the relative standing of an entire sample - by computing a z-score for the sample"s mean. Standard error of the mean the standard deviation of the sampling distribution of means. Finding the probability of sample means: use a sampling distribution of means, a sampling distribution is the frequency distribution of all possible sample means. Sampling error: when random chance produces an unrepresentative sample from a population, with the result that the sample"s statistic is different from the population parameter it represents. Criterion the probability that defines whether a sample is unlikely to represent the underlying raw score population.
