Pearson correlation in SciPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the Pearson correlation coefficient measure?

It measures the strength and direction of a linear relationship between two variables.

beginner

What is the range of values for the Pearson correlation coefficient?

The values range from -1 to 1, where 1 means perfect positive linear correlation, -1 means perfect negative linear correlation, and 0 means no linear correlation.

beginner

How do you calculate Pearson correlation using scipy?

Use scipy.stats.pearsonr(x, y) where x and y are arrays of data. It returns the correlation coefficient and the p-value.

intermediate

What does a p-value returned by scipy.stats.pearsonr indicate?

It indicates the probability that the observed correlation happened by chance. A small p-value (e.g., < 0.05) suggests the correlation is statistically significant.

intermediate

Can Pearson correlation detect non-linear relationships?

No, Pearson correlation only measures linear relationships. Non-linear relationships may have a low or zero Pearson correlation even if variables are related.

What does a Pearson correlation coefficient of 0.8 indicate?

A Strong positive linear relationship

B Strong negative linear relationship

C No linear relationship

D Perfect negative linear relationship

A value of 0.8 means a strong positive linear relationship between the two variables.

Which scipy function calculates Pearson correlation?

A scipy.stats.spearmanr

B scipy.stats.kendalltau

C scipy.stats.ttest_ind

D scipy.stats.pearsonr

scipy.stats.pearsonr calculates the Pearson correlation coefficient and p-value.

What does a p-value less than 0.05 mean in Pearson correlation test?

A No correlation exists

B Correlation is likely due to chance

C Correlation is statistically significant

D Data is not normally distributed

A p-value less than 0.05 suggests the correlation is statistically significant and unlikely due to chance.

What is the Pearson correlation coefficient for no linear relationship?

A 0

B -1

C 0.5

D 1

A coefficient of 0 means no linear relationship between variables.

Can Pearson correlation detect a curved (non-linear) relationship?

A Only if data is large

B No, it only measures linear relationships

C Yes, always

D Only if variables are categorical

Pearson correlation only measures linear relationships and may miss non-linear associations.

Explain how to use scipy to calculate Pearson correlation between two data arrays.

Think about the function name and what it returns.

Describe what the Pearson correlation coefficient tells us about two variables.

Focus on what the number means in terms of relationship.