#### Event Title

T-Test for Proportions? Making Do When Your Software Can't Do Confidence Intervals for Proportions

#### Presentation Type

Poster/Portfolio

#### Presenter Major(s)

Biostatistics, Statistics

#### Mentor Information

Sango Otieno, otienos@gvsu.edu; Gerald Shoultz, shoultzg@gvsu.edu

#### Department

Statistics

#### Location

Kirkhof Center KC23

#### Start Date

13-4-2011 12:00 PM

#### End Date

13-4-2011 1:00 PM

#### Keywords

Mathematical Science

#### Abstract

In Introductory Statistics courses, students are taught how to calculate confidence intervals for the population proportion and the difference between two population proportions. However, statistical software packages often lack syntax for computing such intervals. We assume that if proportion data is recoded in a binary fashion, the resulting t-confidence intervals for one and two sample problems are equivalent to the corresponding z-intervals. We determine mathematically and by simulations, at what sample size, the t and z intervals can be considered equivalent for various confidence levels.

This document is currently not available here.

T-Test for Proportions? Making Do When Your Software Can't Do Confidence Intervals for Proportions

Kirkhof Center KC23

In Introductory Statistics courses, students are taught how to calculate confidence intervals for the population proportion and the difference between two population proportions. However, statistical software packages often lack syntax for computing such intervals. We assume that if proportion data is recoded in a binary fashion, the resulting t-confidence intervals for one and two sample problems are equivalent to the corresponding z-intervals. We determine mathematically and by simulations, at what sample size, the t and z intervals can be considered equivalent for various confidence levels.