Lecture 5

# Lecture 5 - 1 Predicting Parameters Generalize beyond the...

This preview shows pages 1–3. Sign up to view the full content.

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: 1 Predicting Parameters Generalize beyond the data Generalize beyond the data s Statistic s A characteristic of a sample s Parameter s A characteristic of a population s Statistical inference s The process of estimating parameters from statistics Random Sampling s Random sampling s Allows us to use the logic of statistical inferences, that is, estimating parameters from statistics s Random sample s A collection of phenomena so selected that each phenomenon has an equal chance of being selected 2 Three Kinds of Distributions s Sample Distribution s Mean ( M ) and standard deviation ( s ) s Population Distribution s Mean ( μ ) and standard deviation ( σ ) s Sampling Distribution s The distribution of a statistic s Mean ( ) and standard deviation s Standard error of the mean ( σ M ) M Sampling Error s An estimate of how statistics may be expected to deviate from parameters when sampling randomly from a given population....
View Full Document

{[ snackBarMessage ]}

### Page1 / 5

Lecture 5 - 1 Predicting Parameters Generalize beyond the...

This preview shows document pages 1 - 3. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online