Details

Autor(en) / Beteiligte

• Rossman, Allan J.
• Chance, Beth L.

Titel

Confidence Intervals I

Ist Teil von

• Workshop Statistics, p.279-293

Ort / Verlag

New York, NY: Springer New York

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• In the last unit you explored how sample statistics (in particular, sample proportions) vary from sample to sample. The Central Limit Theorem has allowed you to make probability statements about a sample proportion falling in a certain interval, provided that one knows the value of the population proportion. The much more common problem is to estimate or to make a decision about an unknown population parameter based on an observed sample statistic. These are goals of statistical inference. There are two major techniques of classical statistical inference: confidence intervals and tests of significance. Confidence intervals seek to estimate a population parameter with an interval of values calculated from an observed sample statistic. Tests of significance assess the extent to which sample data support a particular hypothesis concerning a population parameter. This topic extends your study of the concept of statistical confidence by introducing you to the construction of confidence intervals for estimating a population proportion.