Exponential regression is a type of regression that can be used to model the following situations:
1. Exponential growth: Growth begins slowly and then accelerates rapidly without bound.
2. Exponential decay: Decay begins rapidly and then slows down to get closer and closer to zero.
The equation of an exponential regression model takes the following form:
y = abx
- y: The response variable
- x: The predictor variable
- a, b: The regression coefficients that describe the relationship between x and y
The following step-by-step example shows how to fit an exponential regression model to the following dataset on a TI-84 calculator:
Step 1: Enter the Data
First, we will enter the data values. Press , then press . Then enter the x-values of the dataset in column L1 and the y-values in column L2:
Step 2: Fit the Exponential Regression Model
Next, we fill fit the exponential regression model.
Press , then scroll over to . Then scroll down to and press twice.
The following results will be displayed:
Step 3: Interpret the Results
From the results we can see that the fitted exponential model is:
y = 1.727 * 1.651x
We can use this equation to predict the response variable, y, based on the value of the predictor variable, x. For example, if x = 4, then we would predict that y would be 12.83:
y = 1.727 * 1.6514 = 12.83
Bonus: Feel free to use this online Exponential Regression Calculator to automatically compute the exponential regression equation for a given predictor and response variable.