Math Problem Statement
Solution
The image presents a problem where you need to find a linear regression model for the men's and women's 100-meter freestyle times based on the provided data. The men's regression model is already given as:
where represents the men's time, and is the number of years since 1992.
To complete the task, let's perform the following steps for the women's dataThe image presents a problem where you need to find a linear regression model for the men's and women's 100-meter freestyle times based on the provided data. The men's regression model is already given as:
where represents the men's time, and is the number of years since 1992.
To complete the task, let's perform the following steps for the women's
- Extract the data points for the women’s 100-meter freestyle times.
- Fit a linear regression model to the women's data.
- Compare the two models and check whether they suggest the women will eventually catch up with the men.
Here is the women's data extracted from the table:
\hline \text{Year (x)} & \text{Women’s Time (y)} \\ \hline 1992 & 54.79 \\ 1996 & 55.92 \\ 2000 & 54.93 \\ 2004 & 54.65 \\ 2008 & 54.50 \\ 2012 & 53.83 \\ 2016 & 53.84 \\ 2020 & 53.12 \\ \hline \end{array}$$ Let me calculate the linear regression equation for the women's times.The linear regression model for the women's 100-meter freestyle times is: $$y = -0.076x + 55.512$$ where: - $$y$$ represents the women's time in seconds. - $$x$$ is the number of years since 1992. ### Comparison of Models: - **Men’s equation**: $$y = -0.145x + 50.523$$ - **Women’s equation**: $$y = -0.076x + 55.512$$ Both models indicate that times are decreasing over the years, but the men’s times are improving faster (with a steeper slope of -0.145) than the women’s times (with a slope of -0.076). This suggests that, while both are improving, the women are not catching up to the men at this rate based on these models. Would you like to explore this further or ask any other questions? ### Here are some related questions you could consider: 1. How do the models predict future performance for men and women? 2. How would the graphs of these two models compare visually? 3. What does the slope represent in the context of the problem? 4. What are potential limitations of using linear regression for this data? 5. Could the women eventually surpass the men, and if so, when? ### Tip: When interpreting a regression model, always check the slope to understand the rate of change over time. A steeper slope means faster improvement or decline.Ask a new question for Free
By Image
Drop file here or Click Here to upload
Math Problem Analysis
Mathematical Concepts
Linear Regression
Statistics
Algebra
Formulas
Linear regression equation y = mx + b
Theorems
Linear regression analysis
Suitable Grade Level
Grades 9-12
Related Recommendation
Linear Regression Model for Men's and Women's 100-Meter Freestyle Times
Linear Regression Models for Men's and Women's 100-Meter Freestyle Times
Linear Regression Model for Men's and Women's 100-Meter Freestyle
Linear Regression Model for Men's and Women's 100-Meter Freestyle Times
Least Squares Line Calculation for Swimming Times in the Women's 100m Freestyle