Fix Incorrect Polynomial Results for Large X Values in Excel
Question details
Users experience highly inaccurate results when calculating polynomial formulas using large X values with visibly rounded trendline coefficients.

- Product
- Excel
- Device & OS
- not provided
- Scenario
- Projecting future values or forecasting data using a polynomial trendline equation derived from a chart, where the input X values are large numbers (such as years like 2013 to 2050).
- Observed behavior
- The polynomial formula yields massively incorrect results (e.g., negative numbers instead of expected positive growth) because tiny rounding discrepancies in the coefficients multiply into massive errors when large X values are squared or cubed.
Ensure you have the original dataset used to generate the trendline chart, as you will need to extract the unrounded mathematical coefficients to correct the formula.
Display Full Precision Coefficients in the Chart Equation
Increase the decimal places of the trendline equation directly on the chart to reduce mathematical rounding errors when plugging in large X values.
By default, Excel visually rounds the coefficients in chart trendline equations. When you manually copy these rounded numbers into a worksheet formula and multiply them by large numbers raised to a power, the small missing decimals cause massive deviations in the final result.
Click on the trendline equation label currently displayed on your Excel chart to highlight it.
Right-click the highlighted equation and select 'Format Trendline Label' from the context menu.
In the Format pane, expand the 'Number' section. Change the Category dropdown from 'General' to 'Number' or 'Scientific'.
Set the decimal places to 15. The equation on the chart will instantly update to show the unrounded, high-precision coefficients.
Manually copy these new, highly precise coefficients into your worksheet formula to correctly calculate the results for large X values.

Calculate Unrounded Coefficients Using the LINEST Function
Generate the polynomial coefficients directly inside your worksheet cells using the LINEST array formula, bypassing the chart's visual rounding entirely.
Normalize Your X Values Before Calculating
Scale down large X values (such as calendar years) into smaller integers to naturally prevent exponentiation multiplier errors.
Accurately Calculate Polynomial Trendlines in WPS Spreadsheet
WPS Spreadsheet provides powerful data analysis tools, including high-precision trendlines and array functions like LINEST, ensuring your complex forecasting is always accurate without unexpected rounding errors.
- 1. Insert a Scatter Chart: Highlight your dataset, navigate to the 'Insert' tab, and click the Scatter chart icon.
- 2. Add a Polynomial Trendline: Right-click on a data point inside the chart, choose 'Add Trendline', and select 'Polynomial' from the right-hand panel.
- 3. Format Data Labels for High Precision: Check 'Display Equation on chart', right-click the equation label, open formatting options, and set the decimal places to 15 for maximum calculation accuracy.

Frequently Asked Questions
Why does my polynomial trendline equation give wrong answers?
Chart equations are visually rounded for readability by default. When large X values (like the year 2049) are squared or cubed, even a 0.0001 rounding difference in the coefficient multiplies into a massive error, sometimes flipping a positive projection into a negative number.
How many decimal places should I use for polynomial coefficients?
It is highly recommended to use the maximum allowed calculation precision, which is 15 decimal places, especially when you are dealing with large input values. You can format the trendline label on the chart to display 'Number' format with 15 decimal places.
Does the LINEST function work for polynomial curves?
Yes. By feeding an array of powers into the X argument (e.g., x_values^{1,2,3} for a 3rd-order polynomial), LINEST will calculate and return the exact, unrounded mathematical coefficients straight into your worksheet cells.
Should I use smaller X values to fix the calculation?
Yes, normalizing X values—for instance, replacing four-digit years like 2020 and 2021 with simple sequences like 1 and 2—drastically reduces exponentiation errors. This makes even rounded chart coefficients much more reliable for future predictions.




