Math Problem Statement

  1. The height (in feet) and volume of usable lumber (in cubic feet) of 32 cherry trees are measured by a researcher. The goal is to determine if volume of usable lumber can be estimated from the height of a tree. The results are plotted below.

(a) In this study, the response variable (y) is

A. volume.

B. height.

C. neither height nor volume. The measuring instrument used to measure height is the response variable.

D. height or volume. It doesn't matter which is considered the response.

The height (in feet) and volume of usable lumber (in cubic feet) of 32 cherry trees are measured by a researcher. The goal is to determine if the volume of usable lumber can be estimated from the height of a tree. The results are plotted in a scatter plot.

Solution

The response variable in a study refers to the outcome or dependent variable, which is what you're trying to predict or explain. In this case, the researcher is attempting to estimate the volume of usable lumber based on the height of the tree. Therefore, the response variable is the volume.

The predictor or explanatory variable is the height, as it is being used to estimate the volume.

Thus, the correct answer is: A. Volume

Would you like further details on this or have any additional questions?

Here are 5 related questions to deepen your understanding:

  1. What is the predictor variable in this scenario?
  2. How can a regression model help in predicting the volume based on the height?
  3. What are some methods to evaluate the accuracy of the regression model in this case?
  4. How would you describe the relationship between height and volume based on the scatter plot?
  5. Could the relationship between height and volume be non-linear? How would you check this?

Tip: Always ensure to label your response and predictor variables correctly when setting up any regression analysis.

Ask a new question for Free

By Image

Drop file here or Click Here to upload

Math Problem Analysis

Mathematical Concepts

Regression Analysis
Scatter Plot
Correlation

Formulas

Linear regression formula: y = mx + b

Theorems

Least Squares Regression Theorem

Suitable Grade Level

Grades 9-12