Part A:
The approximate y-intercept of the line of best fit is 1.8. This represents the number of games won without any months of practice, or in other words, the baseline level of performance without any practice.
Part B:
To find the equation for the line of best fit, we first need to calculate the slope using two of the ordered pairs: (0, 1) and (2, 5).
Slope = (5-1)/(2-0) = 4/2 = 2
Now that we have the slope, we can use the point-slope form of a linear equation to find the equation for the line of best fit:
y - 1 = 2(x - 0)
y - 1 = 2x
y = 2x + 1
Therefore, the equation for the line of best fit in slope-intercept form is y = 2x + 1.
To predict the number of games won after 13 months of practice, we can plug in x = 13 into the equation:
y = 2(13) + 1
y = 26 + 1
y = 27
Therefore, the predicted number of games that could be won after 13 months of practice is 27.
The graph shows the relationship between the number of months different students practiced baseball and the number of games they won:
The title of the graph is Baseball Games. On x axis, the label is Number of Months of Practice. On y axis, the label is Number of Games Won. The scale on the y axis is from 0 to 22 at increments of 2, and the scale on the x axis is from 0 to 12 at increments of 2. The points plotted on the graph are the ordered pairs 0, 1 and 1, 3 and 2, 5 and 3, 9 and 4, 10 and 5, 12 and 6, 13 and 7, 14 and 8,17 and 9, 18 and 10,20. A straight line is drawn joining the ordered pairs 0, 1.8 and 2, 5.6 and 4, 9.2 and 6, 13 and 8, 16.5 and 10, 20.5.
Part A: What is the approximate y-intercept of the line of best fit and what does it represent? (5 points)
Part B: Write the equation for the line of best fit in slope-intercept form and use it to predict the number of games that could be won after 13 months of practice. Show your work and include the points used to calculate the slope. (5 points)
1 answer
1 answer