Question Video: Using Straight Lines to Model Relationships between Two Quantitative Variables | Nagwa Question Video: Using Straight Lines to Model Relationships between Two Quantitative Variables | Nagwa

Question Video: Using Straight Lines to Model Relationships between Two Quantitative Variables Mathematics

The following scatter plot shows the heights and weights of 24 students in a class. Which of the following is true? [A] The data has an outlier. [B] The heavier you are, the shorter you are. [C] There is a negative correlation between height and weight. [D] There is no correlation between height and weight.

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Video Transcript

The following scatter plot shows the heights and weights of 24 students in a class. Which of the following is true? A) The data has an outlier, B) the heavier you are, the shorter you are, C) there is a negative correlation between height and weight, or D) there is no correlation between height and weight.

If we consider the line of best fit on the scatter plot, we can identify the correlation. As the line of best fit slopes upwards from left to right, we can say that there is a positive correlation. This automatically ruled out option C, which stated there is a negative correlation between height and weight, and also option D, which said there is no correlation between height and weight.

The positive correlation in this case means that the heavier you are, the taller you are. This rules out option B, which stated the heavier you are, the shorter you are. This would have been shown by a negative correlation. We are now left with option A: the data has an outlier.

An outlier is a point that doesn’t follow the correlation or pattern. In this case, the person with height 141 centimetres and weight 64 kilograms doesn’t follow the pattern or correlation. Therefore, we can say that that person is an outlier. Out of the four statements, the one that is true is the data has an outlier.

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