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Find the linear trend line of best fit for paired data and predict y values from x
Execution
Fill in the form, run the tool, and review the result in one place.
Samples
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Tool usage guide
The Line of Best Fit Calculator uses linear regression to determine the most accurate trend line for a set of paired data points. By calculating the slope, y-intercept, and R-squared value, it helps users visualize data relationships and predict future outcomes based on specific input variables.
Background
A retail manager has monthly sales data for the first five months of the year and needs to estimate June's performance.
Problem
Predicting future revenue based on a steady upward trend.
How to use
Input the month numbers (1-5) and corresponding sales figures into the Data Pairs field, then set Prediction X to 6.
Outcome
The tool provides the slope of growth and predicts the sales value for month 6.
Background
A researcher is measuring the relationship between temperature and chemical reaction speed.
Problem
Determining the mathematical formula that describes the reaction rate.
How to use
Paste the temperature (x) and speed (y) readings into the calculator and set decimal places to 4 for precision.
Outcome
The calculator returns the linear equation (y = mx + b) and the R-squared value to verify the experiment's consistency.
It is a straight line that best represents the data on a scatter plot by minimizing the distance between the points and the line.
R-squared measures how well the regression line fits the data; a value closer to 1 indicates a stronger linear relationship.
Yes, by entering a Prediction X value, the tool uses the calculated equation to estimate the corresponding Y.
Enter data as comma-separated pairs (e.g., 10, 20) with each pair on a new line.
This specific calculator is designed for linear regression and will find the best straight line regardless of the data's curvature.