**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 Excel.

**Step 1: Enter the Data**

Suppose a restaurant 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: Perform a Two-Factor ANOVA Without Replication**

Next, we’ll perform a two-way ANOVA without replication.

To do so, click the **Data** tab along the top ribbon and then click the **Data Analysis** option under the **Analysis** group:

If you don’t see this option available, you need to first load the Analysis ToolPak.

In the dropdown menu that appears, click **Anova: Two-Factor Without Replication** and then click **OK**. In the new window that appears, fill in the following information and then click **OK**:

The following results will appear:

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

Next, we’ll use the following formula to calculate Cronbach’s Alpha:

Cronbach’s Alpha turns out to be **0.773**.

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 **0.773**, we would say that the internal consistency of this survey is “Acceptable.”

**Bonus:** Feel free to use this Cronbach’s Alpha Calculator to automatically find Cronbach’s Alpha for a given dataset.