Scatter Plots

The video tutorial explains how to identify and interpret correlations between two real-life variables using scatter plots. It covers different types of correlations, such as positive, negative, and no correlation, and discusses the concepts of clusters and outliers. The tutorial also demonstrates how to draw a line of best fit and use it to make predictions by finding the equation in slope-intercept form. The importance of understanding correlations for making informed predictions is emphasized.

What does a positive correlation in a scatter plot indicate?

• The points follow a line with a positive slope.

• The points are randomly scattered with no pattern.

• The points follow a line with a negative slope.

• The points form a perfect circle.

What is an outlier in the context of scatter plots?

• A point that lies exactly on the line of best fit.

• A point that is part of a cluster.

• A point that is far away from most other data points.

• A point that is very close to the line of best fit.

How can a line of best fit be used in scatter plots?

• To eliminate outliers from the data set.

• To approximate the trend and make predictions.

• To show the exact relationship between variables.

• To connect all the data points directly.

What is the first step in using a line of best fit for predictions?

• Calculating the average of all data points.

• Identifying all outliers in the data.

• Finding the equation of the line in slope-intercept form.

• Drawing a perfect line through all points.

In the given example, what is the slope of the line of best fit?

• 1/2

• 2

• 3/2

• 2/3