Name__________________________________________ Period____________
Exponential Regression Curves
1. A basketball is dropped from a height of 200 cm. The table shows how high it bounces on each bounce.
a. Create a scatterplot using the data. Label your graph.
b. Determine the exponential regression curve equation
using GeoGebra.
c. Does it make sense to use the exponential regression curve for extrapolation (predicting the future)?
2. A herd of caribou is moved to a small, remote island where they have no predators. Data on the population
of the population of the herd were collected for 6 years.
a. Create a scatterplot using the data. Label your graph.
b. Find the equation for the Linear Regression line and
Exponential Regression curve. Explain which is a better fit.
c. Describe the growth of the herd.
d. Using the regression of best fit predict the population of the herd after seven years.
The following table shows the purchasing value of the dollar, or the consumer price index, for consumers in
the United States from 1955 to 2010. The table uses the year 1982 as a base period, so the consumer price
index written in dollars and cents in 1982 is 1.00. For instance, in 1955 the consumer price index was 3.73.
This means that a dollar in 1955 was worth 3.73 times what it was worth in 1982. Similarly, a dollar in 2010
was worth 0.46 times what it was worth in 1982.
The scatter plot shows the data in the table where x represents the number of years since 1955 and y
represents the consumer price index.
1. Describe how the consumer price index changes over time.
2. What type(s) of regression do you think fits the data the best? Linear or Exponential?
3. Find the regression equation for the data using GeoGebra.
4. Using the equation predict the consumer price index for the year 2025.