**Chronbach’s Alpha** is a way to measure the internal consistency of a questionnaire or survey.

Cronbach’s Alpha ranges between 0 and 1, with higher values indicating that the survey or questionnaire is more reliable.

The following step-by-step example explains how to calculate Cronbach’s Alpha in Google Sheets.

**Step 1: Enter the Data**

Suppose a store manager wants to measure overall satisfaction among customers.

She decides to send out a survey to 10 customers who can rate the restaurant on a scale of 1 to 3 for various categories.

First, let’s enter the data that contains the survey responses for each of the 10 customers:

**Step 2: Calculate Standard Deviations**

Next, we will calculate the standard deviation of values in each column.

To do so, type the following formula into cell **B12**:

=STDEV(B2:B11)

Then click and drag this formula to the right to cell **E12**:

**Step 3: Calculate Cronbach’s Alpha**

Next, we’ll type the following formula into cell **B14** to calculate Cronbach’s Alpha:

=(COUNTA(B1:D1)/(COUNTA(B1:D1)-1))*(1-(SUMSQ(B12:D12)/(E12^2)))

The following screenshot shows how to use this formula in practice:

Cronbach’s Alpha turns out to be **0.7734**.

The following table describes how different values of Cronbach’s Alpha are usually interpreted:

Cronbach’s Alpha |
Internal consistency |
---|---|

0.9 ≤ α | Excellent |

0.8 ≤ α < 0.9 | Good |

0.7 ≤ α < 0.8 | Acceptable |

0.6 ≤ α < 0.7 | Questionable |

0.5 ≤ α < 0.6 | Poor |

α < 0.5 | Unacceptable |

Since we calculated Cronbach’s Alpha to be **0.7734**, we would say that the internal consistency of this survey is “Acceptable.”

**Additional Resources**

The following tutorials provide additional information about Cronbach’s Alpha:

How to Report Cronbach’ Alpha

How to Calculate Cronbach’s Alpha in R

How to Calculate Cronbach’s Alpha in Python