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1 | 1 | #6. Reliability Analysis |
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7 | 5 | 1. Click on_**Reliability Analysis**_ in the_**Statistics**_ category. |
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13 | 9 | 2._**Data**_: Select the data for Reliability Analysis. You can specify only the data that meets specific conditions from the chosen DataFrame through[_**Subset**_](../data-analysis/5.-subset.md). |
14 | 10 | 3._**Variable**_: Choose the columns for Reliability Analysis from the data selected above. |
15 | 11 | 4._**Code View**_: Preview the code that will be generated. |
16 | 12 | 5._**Data View**_: Preview the data that will be output. |
17 | 13 | 6._**Run**_: Execute the code. |
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| 15 | +###Example Output |
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21 | | -###Output Example |
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27 | 19 | *_**Cronbach Alpha**_ used in Reliability Analysis is a statistical method measuring_**Consistency**_, and this consistency is an indicator of Reliability. |
28 | | -* The Cronbach Alpha value is output between 0 and 1, where closer to 1 indicates higher consistency. The_**N**_ value represents the number of columns selected. |
29 | | -*_**The Item-Total Statistics t**_able displays the mean, variance, and Cronbach Alpha values for each column's presence or absence. Additionally,_**Corrected Item-Total Correlation**_ indicates how consistent each column is with the total. |
| 20 | +***The Cronbach Alpha value** is output between 0 and 1, where closer to 1 indicates higher consistency. The_**N**_ value represents the number of columns selected. |
| 21 | +*_**The Item-Total Statistics t**_**able** displays the mean, variance, and Cronbach Alpha values for each column's presence or absence. Additionally,_**Corrected Item-Total Correlation**_ indicates how consistent each column is with the total. |
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