High School

We appreciate your visit to A regression analysis between weight Y in pounds and height X in inches resulted in the following least squares line Y 128 6X This implies. This page offers clear insights and highlights the essential aspects of the topic. Our goal is to provide a helpful and engaging learning experience. Explore the content and find the answers you need!

A regression analysis between weight (Y in pounds) and height (X in inches) resulted in the following least squares line:

\[ Y' = 128 + 6X \]

This implies that if the height is increased by 1 inch, the weight on average is expected to:

A. Increase by 6 pounds
B. Decrease by 1 pound

Answer :

In the given regression analysis, we have the equation for the least squares line as:

[tex]Y' = 128 + 6x[/tex]

Here, [tex]Y'[/tex] represents the predicted weight in pounds, and [tex]x[/tex] represents the height in inches. The numbers in this equation have specific roles:

  1. The number 128 is the y-intercept, which is the predicted weight when the height is zero inches. While this doesn't have a practical meaning in a real-world context (since no person is 0 inches tall), it is a necessary part of the equation.

  2. The number 6 is the slope of the line, which indicates the change in the predicted value of [tex]Y'[/tex] for a one-unit increase in [tex]x[/tex].

This slope tells us how much the weight is expected to change, on average, when the height increases by 1 inch.

  • Since the slope is 6, it means that for every 1 inch increase in height, the weight is expected to increase by 6 pounds on average.

Therefore, the correct choice is:

  • Increase by 6 pounds.

Thanks for taking the time to read A regression analysis between weight Y in pounds and height X in inches resulted in the following least squares line Y 128 6X This implies. We hope the insights shared have been valuable and enhanced your understanding of the topic. Don�t hesitate to browse our website for more informative and engaging content!

Rewritten by : Barada