Understanding Correlation Coefficient

The video tutorial explains the correlation coefficient, which measures the strength and direction of a relationship between two variables, ranging from -1 to 1. A value of 1 indicates a perfect positive correlation, while -1 indicates a perfect negative correlation. Examples are provided using apple picking and money. The Pearson correlation coefficient, represented by 'R', is introduced, calculated by dividing the covariance by the product of the standard deviations of the variables.

What does the correlation coefficient indicate besides the direction of the relationship between two variables?

• The strength of the relationship

• The units of measurement

• The type of variables

• The number of variables

What is the range of values for the correlation coefficient?

• -1 to 1

• 0 to 1

• 0 to 100

• -1 to 0

What does a correlation coefficient of 1 signify?

• Weak positive correlation

• No correlation

• Perfect inverse proportionality

• Strongest possible positive correlation

In the example given, if you are paid $2 for every apple you pick, what would the correlation coefficient be?

• 0

• 1

• -1

• 0.5

What does a correlation coefficient of -1 indicate?

• Weak inverse correlation

• Perfect direct proportionality

• No correlation

• Strongest possible inverse correlation

What does a correlation coefficient of 0 signify?

• No correlation

• Perfect direct proportionality

• Strongest possible inverse correlation

• Weak positive correlation

Which formula is most popular for calculating the correlation coefficient?

• Kendall's tau

• Spearman's rank correlation

• Chi-square test

• Pearson correlation coefficient

How is the Pearson correlation coefficient calculated?

• By dividing the covariance by the sum of the variables

• By dividing the covariance by the product of the standard deviations of the variables

• By multiplying the covariance by the standard deviation

• By adding the covariance to the standard deviation