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Probability and Samples, Central Limit Theorem - Coggle Diagram
Probability and Samples
Population
Entire group being studied
Sample
Small group selected from a population
Sample Mean
Average score of sample
Distribution of Sample Means
Distribution of all possible sample means
Sampling Error
Difference between sample statistic and population parameter
Samples Vary
Different samples from the same population are usually different
Population Mean
Average score of the whole population
Sample Size
Number of scores in each sample
Many Possible Samples
Population can produce thousands or millions of samples
Random Sample
Sample Selected by chance from a population
Sample Means Differ
Different samples usually have different means
Statistic
Value calculated from a sample
Distribution of Sample Man
Possible sample means from population
Central Limit Theorem
Population Mean
Mean of sample means equals the population mean
Population Standard Deviation
Measures variability in the population
Standard Error
Standard deviation if sample means distribution
Foundation of Inferential Statistics
Used to make predictions about populations from samples
Normal Shape
Distribution becomes more normal as sample size increases
Describes the distribution of sample means