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How-To

Quick Start

Create your first scatter plot in less than two minutes.

This example shows the simplest way to create a scatter plot: two columns of numeric data paired as X and Y, with a linear regression line fitted to the data.

Goal

Create a scatter plot showing the relationship between temperature and yield, with a linear trendline and regression statistics.

Sample Data

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

Temperature Yield
150 77.2
160 78.5
170 81.3
180 84.1
190 85.7
200 88.9
210 90.2
220 93.6
230 94.8
240 97.1

Each row represents one observation with paired Temperature (X) and Yield (Y) values. As temperature increases, yield tends to increase, and the scatter plot will reveal this relationship.

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 → Scatter Plot.

  3. Select your data

    Select cells A1:B11 (the header row plus all 10 data rows).

  4. Configure the analysis

    In the Scatter Plot dialog:

    • X Columns: "Temperature" should be checked
    • Y Columns: "Yield" should be checked
    • Regression: "Linear" should be selected (default)

    Click Finish to generate the chart.

Result

Quantum XL creates a scatter plot with Temperature on the X-axis and Yield on the Y-axis. A linear regression line fits through the data points, showing a clear positive relationship. The statistics table alongside shows:

  • R²: how well the line fits the data (closer to 1 = better fit)
  • Coefficients: the intercept and slope of the regression equation
  • p-values: whether the relationship is statistically significant

A yellow input cell lets you enter a Temperature value to predict the expected Yield.

More Examples

Ready for more? See these variations: