Linear regression in Excel is the foundation of any trend analysis, sensitivity analysis, or what-if model. The five functions below cover most of what everyday regression work needs. The pattern is: identify the relationship (x drives y), fit the line, report the R-squared, predict the future.
The five functions
SLOPE returns the slope of the regression line. Use it when you want to know how much y changes for each unit change in x. INTERCEPT returns the y-intercept - the value of y when x is zero. TREND returns the predicted y for a given x, supporting array formulas. RSQ returns the R-squared - the proportion of variance in y explained by x. LINEST returns a full array of regression statistics.
How to report a regression
The senior reports a regression with three numbers: the slope, the intercept, and the R-squared. The slope answers "how much does y change per unit x?" The intercept answers "what is y when x is zero?" The R-squared answers "how good is the fit?" The senior also plots the data with the regression line overlaid - the chart tells the story the numbers cannot.
The three common pitfalls
Pitfall 1: correlation is not causation. A regression shows that x and y move together, not that x causes y. The senior always investigates the mechanism before acting on a regression. Pitfall 2: outliers distort the line. A single extreme value can pull the slope. The senior always plots the data and checks for outliers before trusting the regression. Pitfall 3: extrapolation is dangerous. The regression is valid for the range of the data; predictions outside the range are unreliable. The senior never forecasts outside the historical range without a caveat.
When to move to Python
Excel linear regression tops out at a few independent variables and a few thousand data points. For multivariate regression, logistic regression, or datasets above 100K rows, the senior moves to Python (scikit-learn, statsmodels). The transition is straightforward - the same model formulation, the same R-squared, just a different tool. The senior uses Excel for standard regressions and Python for anything complex.
