Home / Statistical Tools / Analysis Tools / Summarystats / Preparing Your Data

Preparing Your Data¶

Quantum XL is flexible about data layout. This page explains how different data types behave in Summary Statistics and helps you prepare your data correctly.

How Data Types Work¶

The table below shows what happens when you assign each column type to each role in the Summary Statistics dialog. Click a numbered badge to see an example using that configuration.

		Data Column
		Nominal	Continuous	Integer	Count	DateTime
Frequency Column	None	Not Allowed	Column header names the dataset, statistics computed from all values in the column. One table for all columns. 1 2	Column header names the dataset, statistics computed from all values in the column. One table for all columns.	Column header names the dataset, statistics computed from all values in the column. One table for all columns.	Not Allowed
	Nominal	—
	Continuous	—
	Integer	—
	Count	Not Allowed	Expand dataset by count 3	Expand dataset by count	Expand dataset by count	Not Allowed
	DateTime	—

— indicates this frequency type is not available for selection

Examples¶

1 Quick Start — Statistics for a single data column

2 Multiple Data Columns — Compare statistics across several columns

3 Count Frequency — Pre-aggregated data expanded by count

GroupBy — Compare segments side by side

Data Layout Options¶

Raw Data (One Row Per Observation)¶

Best for most situations. Each row represents a single measurement or observation.

Weight
12.3
15.7
11.2
18.4

Each row is one data point. When you select multiple data columns, each column appears as a separate section in the statistics table.

Pre-Aggregated Data (With Frequency Counts)¶

Use when your data has already been summarized with counts.

Measurement	Frequency
15.3	18
16.1	15
17.8	10

Select Measurement as Data Column and Frequency as Frequency Data. Quantum XL expands the dataset — a row with frequency 18 is treated as 18 observations of that value. The statistics reflect the expanded dataset, not the number of rows.

Common Mistakes¶

Avoid These Issues

Selecting a Nominal or DateTime column as data — Summary Statistics requires numeric data (Continuous, Integer, or Count). Nominal and DateTime columns cannot be used as data columns because statistics like mean and standard deviation are not meaningful for non-numeric data.
Fewer than 2 data points — Standard deviation requires at least 2 observations. Columns with fewer points will show insufficient data for some statistics.
Forgetting that frequency expands the dataset — When using a Count frequency column, the count shown in the statistics reflects the expanded N (sum of all frequencies), not the number of rows in your spreadsheet.
Missing data — Empty cells in data columns are excluded from analysis.