Scatter Plot & Line of Best Fit Practice

Front

What is a scatter plot?

Back

A scatter plot is a graph that shows the relationship between two quantitative variables by displaying data points on a two-dimensional axis.

Front

What does the line of best fit represent in a scatter plot?

Back

The line of best fit represents the trend of the data points in a scatter plot, showing the overall direction of the relationship between the variables.

Front

What is the y-intercept in the context of a line of best fit?

Back

The y-intercept is the point where the line of best fit crosses the y-axis, indicating the value of y when x is zero.

Front

How do you determine if a scatter plot is linear or nonlinear?

Back

A scatter plot is linear if the data points can be approximated by a straight line; it is nonlinear if the data points show a curved pattern.

Front

What does a positive association in a scatter plot indicate?

Back

A positive association indicates that as one variable increases, the other variable also tends to increase.

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What does a negative association in a scatter plot indicate?

Back

A negative association indicates that as one variable increases, the other variable tends to decrease.

Front

What is the equation of a line in slope-intercept form?

Back

The equation of a line in slope-intercept form is y = mx + b, where m is the slope and b is the y-intercept.

Front

How can you identify the slope of a line of best fit?

Back

The slope of the line of best fit can be identified by calculating the change in y divided by the change in x (rise over run) between two points on the line.

Front

What does it mean if there are many data points above the line of best fit?

Back

If there are many data points above the line of best fit, it suggests that the model may underestimate the values of the dependent variable.

Front

What does it mean if there are many data points below the line of best fit?

Back

If there are many data points below the line of best fit, it suggests that the model may overestimate the values of the dependent variable.