---
title: Numeric Factors
category: Preparation
slug: numeric-factors
blurb: Learn how to combine multiple columns into one composite numeric score.
order: 11
---
# Numeric Factors

Numeric Factors let you combine related columns into a single score.  
They are useful anywhere you want one composite metric from multiple inputs, including:
- Rating-style questions (e.g. satisfaction or agreement items)
- Frequency/behavior measures (e.g. usage across several actions)
- Readiness or maturity indices (e.g. process, capability, adoption)
- Experience or risk scores built from multiple indicators

You create a new calculated column, choose the source columns, and control how the factor is calculated.

![Numeric factors walkthrough](https://player.mux.com/bBY26nBAF1Np9QCwX01AetI6TLopQZrsrODmNoWrvXUI)

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## Where to find it

1. From the dashboard, click **More**.
2. Click **Calculated Column**.
3. Choose **Numeric Factor**.
4. Click **Continue**.

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## Before you start

Numeric Factors work best when:
- Your selected columns measure the same concept.
- Higher values should generally mean "more" of that concept.
- You select at least 2 source columns.

Supported source column types include opinion scale columns, numeric columns, and categorical columns that have assigned numbers.

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## How to create a Numeric Factor

1. Enter a **column name** (for example, `Combined Ratings`).
2. Under **Source Columns**, select all questions you want to include.
3. In **Reverse scoring**, enable reverse scoring for items where higher values are actually negative.
4. Choose **Aggregate method**:
   - **Mean**: sensitive to small differences.
   - **Median**: more robust to extreme responses.
5. Set **Minimum answered columns per row**:
   - **Require all selected**: strict, most complete.
   - **Require at least _N_ columns**: allows partial completion.
6. (Optional) enable **Normalize result to 0-100**.
7. Review **Live reliability (Cronbach's alpha)**.
8. Click **Continue**, check the preview, then click **Create Column**.

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## Understanding the key options

### Reverse scoring

Use this when a question is phrased in the opposite direction.

Example:
- "I find this process easy" (higher is positive)
- "I find this process frustrating" (higher is negative)

If both are included in one factor, reverse-score the negative item so all columns point in the same direction.

### Aggregate method (Mean vs Median)

- **Mean** is best when you want every response shift to influence the score.
- **Median** is best when you want a stable center score that is less affected by extreme values.

### Minimum answered columns

This controls missing-data behavior:
- **Require all selected** gives stricter, cleaner factor scores but may exclude more rows.
- **Require at least N** keeps more rows by allowing partially answered item sets.

### Normalize result to 0-100

Enable this when source columns have different scales (for example, one item is 1-5 and another is 0-10). AddMaple rescales each selected item before combining, so the final factor stays on a consistent 0-100 scale.

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## Reliability check (Cronbach's alpha)

Numeric Factor setup shows a live **Cronbach's alpha** estimate:
- Higher alpha generally means the selected items move together consistently.
- Very low alpha can indicate your selected columns are not measuring the same underlying concept.

Use this as a quick quality check before finalizing the column. In plain terms, if this score is low, your selected questions may not belong in one combined score.

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## Example workflows

You have 6 experience ratings:
- Ease of use
- Reliability
- Speed
- Value for money
- Support quality
- Overall satisfaction

You can combine all six into one factor called `Combined Ratings`, normalize to 0-100, and then use that new numeric column in pivots, charts, filters, and comparisons like any other numeric field.

Another common use is a product-adoption score:
- Weekly usage frequency
- Feature breadth used
- Self-reported confidence
- Task completion speed

Even when these come from different scales, you can normalize to 0-100 so each input contributes comparably.

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## Key points

- Numeric Factors create one reusable numeric score from multiple related columns.
- Reverse scoring is important for negatively worded items.
- Missing-data rules (`Require all` vs `Require at least`) can materially change coverage.
- Cronbach's alpha helps validate whether your selected items belong together.

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