Understanding Scatter Graphs: Identifying Correlations and Making Predictions

The video tutorial explains the use of scatter graphs to identify relationships between data sets. It covers positive, negative, and no correlation, and how these can be visualized on a graph. The tutorial also discusses the use of scatter graphs for making predictions through interpolation and extrapolation, using a line of best fit.

What does a positive correlation indicate in a scatter graph?

• As one variable increases, the other decreases.

• There is no relationship between the variables.

• The variables are unrelated.

• As one variable increases, the other also increases.

Which of the following is an example of negative correlation?

• The further you travel, the less petrol you have.

• The more you study, the higher your grades.

• The more you exercise, the more calories you burn.

• The more you eat, the hungrier you get.

What does 'no correlation' mean in the context of scatter graphs?

• Both variables increase together.

• One variable increases while the other decreases.

• There is no link between the two variables.

• The variables are inversely related.

What is the purpose of a line of best fit in a scatter graph?

• To show the exact relationship between variables.

• To predict values within and outside the data set.

• To connect all data points exactly.

• To highlight the outliers in the data.

What is the difference between interpolation and extrapolation?

• Interpolation predicts values within the data set, while extrapolation predicts outside.

• Both predict values within the data set.

• Interpolation predicts values outside the data set, while extrapolation predicts within.

• Both predict values outside the data set.