beyond the numbers BEYOND THE NUMBERS 1.28 LEARNING OUTCOMES 8 TO 10 Read AlI Ab
ID: 3069978 • Letter: B
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beyond the numbers BEYOND THE NUMBERS 1.28 LEARNING OUTCOMES 8 TO 10 Read AlI About It: Correlation and Causation-Correlation Coefficient Read the following content material or watch the video that is available online. There are questions at the end of this reading to answer and turn in Introduction and Definition The scatterplot of heights versus weights is clearly showing a relationship that is positive and fairly strong. But how strong is it? s a word that is used by just about everyone, the "correlation coefficient is a particular, between useful comparison with other associations numerical way of summarizing the strength of the association exhibited two variables that you could legitimately represent in a scatterplot. This is a exercise because it summarizes the strength of the association on a scale that allows Adults: Height versus Weight 75 70 65 60 100 150 200 Weight (pounds The comp can be calculated lex expression you see below is one convenient way that the correlation coefficient We will illustrate on a small data set. But before we do, let's make sure we understand some important facts about the correlation coefficient (continued) 87 BEYONDTHE NUMBERS 1.28Explanation / Answer
1. Correlation coefficient measures numerically the strength of the linear relationship/association between the two variables.
2. Correlation coefficient = -0.95 indicates strong negative linear association between the variables since the value is close to 1 which indicates the strong association and negative value indicates the negative association (one increases other decreases).
The scatterplot is likely to have most data points clustered along a negatively sloped straight line.
3. Using the formula, r = 0.7626.
4. Computation of r will be appropriate if it is not calculated over repeated measurements data or tineseries data or causation relationship.
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