Internal consistency reliability is the extent to which the measurements of a test remain consistent over repeated tests of the same subject under identical conditions. An experiment is reliable if it yields consistent results of the same measure, i.e. it doesn’t yield random error in measurement. It is unreliable if repeated measurements give different results.

Since there are inaccuracies when taking measurements, even when the same measurements are taken twice there can be differences. We can therefore partition an observed value of *x* into the true value of *x* and an error term. Thus we have *x = t + e.*

**Definition 1**: The **reliability** of *x* is a measure of internal consistency and is the correlation coefficient *r _{xt}* of

*x*and

*t*.

Proof: See Proof of Basic Property

- Split-Half Methodology
- Kuder and Richardson Formula 20
- Cronbach’s Alpha
- Cohen’s Kappa
- Weighted Cohen’s Kappa
- Fleiss’ Kappa
- Intraclass Correlation
- Kendall’s Coefficient of Concordance (W)
- Bland-Altman Analysis
- Item Analysis

This is awsum Pack for the statistical calculation. Thanks for it.

Thanks to Mr.Charles Zaiontz for his elaborate examples that are making life easy for us to learn how to analyse our research data using Excel scientific packages.

Please keep it up.

This website is recommended especially for students and Professors in Measurement and Testing. Very helpful indeed.