Scatter Plot Review

Front

What is a scatter plot?

Back

A scatter plot is a graphical representation of two variables where each point represents an observation. It helps to visualize the relationship between the variables.

Front

What does the correlation coefficient (r) indicate in a scatter plot?

Back

The correlation coefficient (r) indicates the strength and direction of a linear relationship between two variables. It ranges from -1 to 1.

Front

What does an r value of -0.981 suggest about the relationship between the variables?

Back

An r value of -0.981 suggests a strong negative correlation, meaning that as one variable increases, the other variable tends to decrease.

Front

What is a positive correlation?

Back

A positive correlation occurs when two variables move in the same direction; as one variable increases, the other variable also increases.

Front

What is a negative correlation?

Back

A negative correlation occurs when two variables move in opposite directions; as one variable increases, the other variable decreases.

Front

How can a trend line be used in a scatter plot?

Back

A trend line can be used to predict values and identify the general direction of the data points in a scatter plot.

Front

What does it mean if a scatter plot shows no correlation?

Back

If a scatter plot shows no correlation, it means there is no discernible relationship between the two variables; the points are scattered randomly.

Front

How do you interpret the slope of a trend line in a scatter plot?

Back

The slope of a trend line indicates the rate of change between the two variables; a positive slope indicates a positive correlation, while a negative slope indicates a negative correlation.

Front

What is the significance of outliers in a scatter plot?

Back

Outliers are data points that differ significantly from other observations. They can affect the correlation and the slope of the trend line.

Front

What is the purpose of using scatter plots in data analysis?

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Scatter plots are used to visualize relationships between variables, identify trends, and detect outliers in data.