# Cronbach’s Alpha

Quantitative Results
Statistical Analysis

Cronbach’s alpha is a convenient test used to estimate the reliability, or internal consistency, of a composite score. Now, what on Earth does that mean? Let’s start with reliability. Say an individual takes a Happiness Survey. Your happiness score would be highly reliable (consistent) if it produces the same or similar results when the same individual re-takes your survey, under the same conditions. However, say an individual, who, at the same level of real happiness, takes this Happiness Survey twice back-to-back, and one score shows high happiness and the other score shows low happiness—that measure would not be reliable at all.

Cronbach’s alpha gives us a simple way to measure whether or not a score is reliable. It is used under the assumption that you have multiple items measuring the same underlying construct: so, for the Happiness Survey, you might have five questions all asking different things, but when combined, could be said to measure overall happiness.

Theoretically, Cronbach’s alpha results should give you a number from 0 to 1, but you can get negative numbers as well. A negative number indicates that something is wrong with your data—perhaps you forgot to reverse score some items. The general rule of thumb is that a Cronbach’s alpha of .70 and above is good, .80 and above is better, and .90 and above is best.

Cronbach’s alpha does come with some limitations: scores that have a low number of items associated with them tend to have lower reliability, and sample size can also influence your results for better or worse. However, it is still a widely used measure, so if your committee is asking for proof that your instrument was internally consistent or reliable, Cronbach’s alpha is a good way to go!

### Need help with your research?

Schedule a time to speak with an expert using the calendar below.

Statistics Solutions can assist with your quantitative analysis by assisting you to develop your methodology and results chapters. The services that we offer include:

Data Analysis Plan

Edit your research questions and null/alternative hypotheses

Write your data analysis plan; specify specific statistics to address the research questions, the assumptions of the statistics, and justify why they are the appropriate statistics; provide references

Justify your sample size/power analysis, provide references

Explain your data analysis plan to you so you are comfortable and confident

Quantitative Results Section (Descriptive Statistics, Bivariate and Multivariate Analyses, Structural Equation Modeling, Path analysis, HLM, Cluster Analysis)

Clean and code dataset

Conduct descriptive statistics (i.e., mean, standard deviation, frequency and percent, as appropriate)

Conduct analyses to examine each of your research questions

Write-up results

Provide APA 6th edition tables and figures

Explain chapter 4 findings

Ongoing support for entire results chapter statistics

Please call 727-442-4290 to request a quote based on the specifics of your research, schedule using the calendar on t his page, or email [email protected]