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How-To

Quick Start

Create your first Cpk/Histogram in less than two minutes.

This example shows the simplest way to create a Cpk/Histogram: a single column of numeric data with specification limits. Quantum XL creates a histogram, overlays normal curves, shows specification limit lines, and calculates capability indices.

Two Ribbon Buttons

You can access this tool from two ribbon buttons: Histogram and Capability Analysis. The Histogram button defaults to showing histogram bars without PDF curves. The Capability Analysis button defaults to showing PDF curves without histogram bars. To see both the histogram and PDF curves together, enable the missing option in the Chart Options tab before clicking Finish.

Goal

Create a Cpk/Histogram showing process capability for diameter measurements with LSL = 9.5 and USL = 10.5.

Sample Data

Press Copy for Excel, then paste the table into a blank worksheet.

Diameter
9.82
10.05
9.97
10.12
9.91
10.08
9.88
10.15
9.95
10.03

Each row represents one diameter measurement. The values are centered around 10.0, and we want to assess whether the process is capable of staying within the specification limits of 9.5 to 10.5.

Steps

  1. Put the data in Excel

    Press Copy for Excel above the table, click cell A1 in a blank worksheet, and press Ctrl+V. The header row lands in row 1 and the 10 data rows in rows 2 through 11.

  2. Launch the analysis

    From the Excel ribbon, select QXL Stat Tools → Analysis Tools → Create Histogram.

  3. Select your data

    Select cells A1:A11 (the header row plus all 10 data rows).

  4. Configure the analysis

    In the Cpk/Histogram dialog:

    • Data Columns: "Diameter" should be checked
    • Specification Limits: Enter LSL = 9.5 and USL = 10.5 for the Diameter column

    Click Finish to generate the chart.

Result

Quantum XL creates a histogram showing the distribution of diameter measurements. Red vertical lines mark the LSL (9.5) and USL (10.5). Normal curves (within and overall standard deviation) are overlaid on the histogram. A statistics table alongside shows:

  • Capability indices: Cp, Cpk, Pp, Ppk values indicating how well the process fits within specs
  • PPM: Parts per million predicted to fall outside specifications
  • Descriptive statistics: Mean, standard deviation, count, min, max

More Examples

Ready for more? See these variations:

  • Multiple Data Columns: Assess capability for multiple measurements with different spec limits
  • GroupBy: Compare capability across machines or shifts