Epidemiology and Biostatistics pp 163-170 | Cite as

# Introduction to Statistical Inference

## Learning Objectives

- 1.
A sample is a subset of individuals derived from a given population.

- 2.
Statistical inference relates findings from a sample to those in the population.

- 3.
Generalizability refers to the scientific/practical relevance of the underlying population.

- 4.Factors that increase the likelihood that sample findings reflect those of the population:
- a.
Large sample size

- b.
Small population variation

- a.
- 5.95% confidence intervals:
- (a)
If a study is repeated indefinitely and a 95% confidence interval placed around each sample mean, then 95% of the intervals will contain the true population mean.

- (b)
Can be calculated without knowing the true population mean.

- (c)
Will be narrower when the sample size is large and the sample variation is small.

- (a)
- 6.
*P*-values:- (a)
Given a null hypothesis

*regarding the population*, the*p*-value is the probability of observing the sample result, or a more extreme result, due to sampling variation. - (b)
Findings from a particular sample are used to make an inference about the true results in the population.

- (a)