Math Problem Statement
Determine the linear regression equation that models the set of data above, and use this equation to answer the following questions: Based on this regression model, what was the value of the investment in 1993, and what is the rate of change of the investment per year?
Solution
It looks like you need help with a linear regression problem based on the table shown in your homework. The table provides the value of an investment for different years after 1993.
To solve this, we'll need to:
- Determine the linear regression equation for the data provided.
- Use the regression equation to find the value of the investment in 1993 (i.e., when ).
- Find the rate of change of the investment value per year (slope of the regression line).
I will begin by calculating the linear regression equation for this dataset.
The table:
\hline n & V(n) \\ \hline 1 & 16385 \\ 3 & 15439.9 \\ 7 & 14495 \\ 12 & 13307.6 \\ 14 & 12290 \\ 19 & 10179.25 \\ \hline \end{array}$$ Let me calculate the regression equation for you.The linear regression equation for the data is: $$V(n) = -324.06n + 16707.33$$ - The **value of the investment in 1993** (when $$n = 0$$) is approximately **\$16,707.33**. - The **rate of change of the investment** is approximately **\$324.06** per year, meaning the investment decreases by this amount each year. Would you like more details, or do you have any specific questions about this problem? ### Related Questions: 1. What does the negative slope imply about the investment over time? 2. How would you find the value of the investment for $$n = 10$$ years? 3. Can you calculate how many years it would take for the investment to reach \$5,000? 4. How accurate is this model for large values of $$n$$, such as 30 or 40 years after 1993? 5. How would the results change if the rate of decrease wasn't constant? ### Tip: When interpreting regression results, always check the sign of the slope to understand whether the trend is increasing or decreasing over time.Ask a new question for Free
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Math Problem Analysis
Mathematical Concepts
Linear Regression
Algebra
Statistics
Formulas
Linear regression equation: y = mx + b
Slope (m) formula: m = Σ[(x - x̄)(y - ȳ)] / Σ[(x - x̄)^2]
Intercept (b) formula: b = ȳ - m*x̄
Theorems
Least squares method for fitting a regression line
Suitable Grade Level
High School (Grades 10-12) or College Introductory Level