Day 42 – Understanding Correlation Coefficient

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Presentation transcript:

Day 42 – Understanding Correlation Coefficient

Vocabulary Strong correlation - means that one value is highly dependent on another value or if the correlation is closely to positive (+) or negative (-) one. Weak correlation - means that one value is NOT highly dependent on another value or if the correlation is likely close to zero.

Key concept The correlation coefficient can tell us a lot about the data that we are examining. Remember that the closer the numbers are to +1 the more the numbers look like a straight line with a positive trend. Remember that the closer the numbers are to -1 the more the numbers look like a straight line with a negative trend.

3 Examples 1. The correlation coefficient between two variables is 0.898. How would you describe this value? (A) Strong and positive (B) Strong and negative (C) Weak and positive (D) Weak and negative

3 Examples 2. The correlation coefficient between two variables is -0.4. How would you describe this value? (A) Strong and positive (B) Strong and negative (C) Weak and positive (D) Weak and negative

3 Examples 3. Which of the following values for r suggests a strong negative correlation? (A) -0.2 (B) 0.95 (C) -0.85 (D) 0

1. Which of the following is true about the data represented below? Try it yourself 1. Which of the following is true about the data represented below? (A) The correlation coefficient is greater than zero. (B) The data depicts a negative weak correlation. (C) The data depicts a negative strong correlation. (D) There is no substantial correlation between the data.

Try it yourself 2. The following figure displays a graph showing work hours and rewards score. Based on the scatter plot, which of the following is the best assumption about the correlation between the variables? (A) Positive linear correlation (B) No correlation (C) Negative linear correlation (D) Exponential correlation