Unit 8: Scatterplots and Associations

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 does it mean if a scatterplot shows no relationship?

Back

It means that there is no discernible pattern or correlation between the two variables being plotted.

Front

How can you identify a linear relationship in a scatterplot?

Back

A linear relationship can be identified if the data points form a straight line or a pattern that closely resembles a straight line.

Front

What is the difference between linear and non-linear relationships?

Back

Linear relationships can be represented by a straight line, while non-linear relationships cannot and may curve or change direction.

Front

What is the purpose of using scatterplots in data analysis?

Back

Scatterplots are used to visually assess the relationship between two variables, helping to identify trends, correlations, and potential outliers.

Front

What does it mean if a scatterplot is described as 'non-linear and positive'?

Back

It means that the data points show a positive trend, but the relationship does not form a straight line.

Front

What is the significance of the slope in a linear scatterplot?

Back

The slope indicates the rate of change between the two variables; a positive slope means both variables increase together, while a negative slope means one variable increases as the other decreases.

Front

How can you determine the strength of a relationship in a scatterplot?

Back

The strength of a relationship can be determined by how closely the data points cluster around a line; tighter clustering indicates a stronger relationship.