Correlation coefficient with np.corrcoef() in NumPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the correlation coefficient measure?

It measures the strength and direction of a linear relationship between two variables, ranging from -1 (perfect negative) to 1 (perfect positive).

beginner

What is the purpose of np.corrcoef() in numpy?

It calculates the correlation coefficient matrix between input arrays, showing how variables relate linearly.

beginner

How do you interpret a correlation coefficient of 0?

It means there is no linear relationship between the two variables, but they might still have other types of relationships.

intermediate

What shape of output does np.corrcoef() return when given two 1D arrays?

It returns a 2x2 matrix where diagonal elements are 1 (correlation of each variable with itself) and off-diagonal elements are the correlation coefficients between the two variables.

intermediate

Why is it important to check correlation before building a predictive model?

Because strong correlations can indicate important relationships between variables, helping to select features and understand data patterns.

What is the range of values for the correlation coefficient?

A -1 to 1

B 0 to 1

C -100 to 100

D 0 to infinity

The correlation coefficient ranges from -1 (perfect negative) to 1 (perfect positive).

What does np.corrcoef(x, y) return when x and y are 1D arrays?

A A list of correlation values

B A single correlation value

C A 2x2 matrix of correlation coefficients

D An error

It returns a 2x2 matrix showing correlations between x and y and themselves.

If the correlation coefficient between two variables is close to 0, what does it mean?

A No linear relationship

B Strong positive relationship

C Strong negative relationship

D Perfect correlation

A value near 0 means no linear relationship between variables.

Which numpy function is used to calculate correlation coefficients?

A np.cov()

B np.corrcoef()

C np.mean()

D np.std()

np.corrcoef() calculates correlation coefficients.

What does a correlation coefficient of -1 indicate?

A Random relationship

B No relationship

C Perfect positive linear relationship

D Perfect negative linear relationship

A value of -1 means a perfect negative linear relationship.

Explain how to use np.corrcoef() to find the correlation between two data arrays.

Think about what the matrix elements represent.

Describe what the correlation coefficient tells us about the relationship between two variables.

Consider how close the value is to 1 or -1.