# Spectrum Math Grade 8 Chapter 6 Lesson 3 Answer Key Fitting Lines to Scatter Plots

Students can use the Spectrum Math Grade 8 Answer Key Chapter 6 Lesson 6.3 Fitting Lines to Scatter PlotsĀ as a quick guide to resolve any of their doubts

## Spectrum Math Grade 8 Chapter 6 Lesson 6.3 Fitting Lines to Scatter Plots Answers Key

When bivariate data is graphed on a scatter plot, it may have a positive or negative association. A trend line can be used to make predictions about values that are not included in the data set. The accuracy of the prediction will depend on how closely the trend line fits the data points.

Create a trend line by using a straight edge to draw a line across the points on a scatter plot. Attempt to have the same number of points above and below the trend line while ignoring outliers.
Based on this trend line, at a distance of 3.5 miles, the Distance (mi| time should be about 37 minutes.

Create a trend line for each scatter plot shown below.

Question 1.
a.

Explanation:
A trend line can be used to make predictions about values that are not included in the data set. The accuracy of the prediction will depend on how closely the trend line fits the data points. The data is graphed on a scatter plot as shown, it may have a positive or negative association. A trend line by using a straight edge to draw a line across the points on a scatter plot.
To have the same number of points above and below the trend line while ignoring outliers.
Based on this trend line drawn in the above plot, the number of pages increases, the chapters also increases.

b.

Explanation:
A trend line can be used to make predictions about values that are not included in the data set. The accuracy of the prediction will depend on how closely the trend line fits the data points. The data is graphed on a scatter plot, it may have a positive or negative association.
AĀ trend line by using a straight edge to draw a line across the points on a scatter plot.
To have the same number of points above and below the trend line while ignoring outliers.
Based on this trend line drawn in the above plot, the value of the CDs sold decreases, as the years increases.

Question 2.
a.

Explanation:
A trend line can be used to make predictions about values that are not included in the data set. The accuracy of the prediction will depend on how closely the trend line fits the data points. The data is graphed on a scatter plot, it may have a positive or negative association.
A trend line by using a straight edge to draw a line across the points on a scatter plot.
To have the same number of points above and below the trend line while ignoring outliers.
Based on this trend line drawn in the above plot, the number of study hours increases, the grade increases.

b.

Explanation:
A trend line can be used to make predictions about values that are not included in the data set. The accuracy of the prediction will depend on how closely the trend line fits the data points. The data is graphed on a scatter plot, it may have a positive or negative association.
A trend line by using a straight edge to draw a line across the points on a scatter plot.
To have the same number of points above and below the trend line while ignoring outliers.
Based on this trend line drawn in the above plot, the average ticket price increases, the year changes.

Question 3.
a.

Explanation:
A trend line can be used to make predictions about values that are not included in the data set. The accuracy of the prediction will depend on how closely the trend line fits the data points. The data is graphed on a scatter plot, it may have a positive or negative association.
A trend line by using a straight edge to draw a line across the points on a scatter plot.
To have the same number of points above and below the trend line while ignoring outliers.
Based on this trend line drawn in the above plot, the value of Y increases, with respect to the value of X increases.

b.

Explanation:
A trend line can be used to make predictions about values that are not included in the data set. The accuracy of the prediction will depend on how closely the trend line fits the data points. The data is graphed on a scatter plot, it may have a positive or negative association.
A trend line by using a straight edge to draw a line across the points on a scatter plot.
To have the same number of points above and below the trend line while ignoring outliers.
Based on this trend line drawn in the above plot, the value of TV hours decreases, the test score increases.

Create a trend line for each scatter plot shown below. Then, make a prediction about the value of one variable given one value of the other variable.

Question 1.
a.

If a student does 80 minutes of homework, predict his grade.

Explanation:
A trend line can be used to make predictions about values that are not included in the data set. The accuracy of the prediction will depend on how closely the trend line fits the data points. The data is graphed on a scatter plot, it may have a positive or negative association.
A trend line by using a straight edge to draw a line across the points on a scatter plot.
To have the same number of points above and below the trend line while ignoring outliers.
Based on this trend line drawn in the above plot, the minutes of homework increases, the math grades % increases.
If a student does 80 minutes of homework, his grade is 90%.

b.

If the water is measured at 13 minutes, predict its depth.

Explanation:
A trend line can be used to make predictions about values that are not included in the data set. The accuracy of the prediction will depend on how closely the trend line fits the data points. The data is graphed on a scatter plot, it may have a positive or negative association.
A trend line by using a straight edge to draw a line across the points on a scatter plot.
To have the same number of points above and below the trend line while ignoring outliers.
Based on this trend line drawn in the above plot, the depth increases, the time increases.
If the water is measured at 13 minutes, its depth 25 cm.

Question 2.
a.

If someone is 106 cm tall, predict his/her foot length.

Explanation:
A trend line can be used to make predictions about values that are not included in the data set. The accuracy of the prediction will depend on how closely the trend line fits the data points. The data is graphed on a scatter plot, it may have a positive or negative association.
A trend line by using a straight edge to draw a line across the points on a scatter plot.
To have the same number of points above and below the trend line while ignoring outliers.
Based on this trend line drawn in the above plot, the foot length and the height increases.
If someone is 106 cm tall, his/her foot length is 15.5 cm.

b.

If the plant Ā”s measured at 15 weeks, predict its height.

Explanation:
A trend line can be used to make predictions about values that are not included in the data set. The accuracy of the prediction will depend on how closely the trend line fits the data points. The data is graphed on a scatter plot, it may have a positive or negative association.
A trend line by using a straight edge to draw a line across the points on a scatter plot.
To have the same number of points above and below the trend line while ignoring outliers.
Based on this trend line drawn in the above plot, the height increases, the time increases.
If the plant is measured at 15 weeks, the height is 32 cm.

Question 3.
a.

If a person spends 17 hours a week exercising, predict her BMI.

Explanation:
A trend line can be used to make predictions about values that are not included in the data set. The accuracy of the prediction will depend on how closely the trend line fits the data points. The data is graphed on a scatter plot, it may have a positive or negative association.
A trend line by using a straight edge to draw a line across the points on a scatter plot.
To have the same number of points above and below the trend line while ignoring outliers.
Based on this trend line drawn in the above plot, the BMI decreases, as the Time exercising increases. If a person spends 17 hours a week exercising, her BMI decreases to 10.

b.

If a server spends 12 hours a week working, predict the tips he will earn.