Scatterplot Predictions

Front

What is a scatterplot?

Back

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

Front

What does a positive association in a scatterplot indicate?

Back

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

Front

What does a negative association in a scatterplot indicate?

Back

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

Front

What is the line of best fit?

Back

The line of best fit is a straight line that best represents the data on a scatterplot, showing the general direction of the data points.

Front

How can you determine the correlation from a scatterplot?

Back

You can determine the correlation by observing the direction and strength of the data points' clustering: tightly clustered points indicate a strong correlation, while widely scattered points indicate a weak correlation.

Front

What does it mean if a scatterplot has no correlation?

Back

No correlation means that there is no apparent relationship between the two variables; the data points are scattered randomly.

Front

How do you interpret the slope of the line of best fit?

Back

The slope indicates the rate of change between the two variables; a positive slope means an increase in the dependent variable as the independent variable increases.

Front

What is the purpose of using a scatterplot?

Back

Scatterplots are used to visually represent the relationship between two variables, making it easier to identify trends, correlations, and outliers.

Front

What is an outlier in a scatterplot?

Back

An outlier is a data point that lies far away from the other points in the scatterplot, which may indicate an unusual observation.

Front

How can you predict values using a scatterplot?

Back

You can predict values by using the line of best fit to estimate the dependent variable based on a given independent variable.