Title: Inferential Statistics - Overview, Parameters, Testing Methods
Headings: Inferential Statistics
Inferential Statistics
What is Inferential Statistics?
Summary
Population Parameters, Sample Statistics, Sampling Errors, and Confidence Intervals
Hypothesis Testing
Other Testing Methods
More Resources

Content: To minimize the uncertainty created by the presence of sampling errors, probability sampling methods can be applied in data analysis. Confidence intervals allow for interval estimations for population values (or parameters) by utilizing statistical variabilities. Confidence intervals account for sampling errors
Sampling Errors Sampling errors are statistical errors that arise when a sample does not represent the whole population. They are the difference between the
. Confidence intervals, as with interval estimates, provide a range of values in which a parameter is likely to be found, and therefore, show the likelihood of point estimate uncertainty. Point estimates and confidence intervals can be used in combination to produce better results. Every confidence interval is accompanied by a confidence level, which indicates the probability of the interval. A 95% (percent) confidence interval shows that if the same study is conducted numerous times with a completely new sample each time, it is likely that 95% of the studies will have an estimate that lies within the same range of values. It applies to estimates and not necessarily to parameters. To know more about different statistics concepts, check out CFI’s Statistics Fundamentals course!