You are a machine learning specialist working for a clothing manufacturer. You have been tasked with building a machine learning model to determine the return on investment (ROI) for advertising a specific clothing line on social media based on the labeled data of past social media campaigns for similar clothing lines.
You decide to run a Pearson’s correlation coefficient to understand your data correlation in a better way. When you calculate your Pearson’s correlation coefficient of social media advertising ROI, you get a value of 0.35. What conclusions can you draw from this result?

Answer options:

A.There is a favorable relationship between your past social media advertising and corresponding campaign ROI.
B.There is an unfavorable relationship between your past social media advertising and corresponding campaign ROI.
C.There is no correlation between past social media advertising and the associated ROI.
D.You cannot declare a notable correlation with confidence based on the resulting coefficient.

Answer: D
Option A is incorrect. Your coefficient value is not high enough to indicate a positive relationship. For a Pearson’s correlation coefficient to indicate a notable correlation, the coefficient value should be above 0.5 for a positive correlation, or below -0.5 for a negative correlation. Your score is 0.35, which falls into the indeterminate range.
Option B is incorrect. Your coefficient value is not low enough to indicate a negative relationship. For a Pearson’s correlation coefficient to indicate a notable correlation, the coefficient value should be above 0.5 for a positive correlation, or below -0.5 for a negative correlation. Your score is 0.35, which falls into the indeterminate range.
Option C is incorrect. A coefficient value of 0 or close to 0 indicates no correlation. Your value of 0.35 is not close enough to 0 to indicate no correlation.
Option D is correct. Your coefficient falls into the indeterminate range. For a Pearson’s correlation coefficient to indicate a notable correlation, the coefficient value should be above 0.5 for a positive correlation, or below -0.5 for a negative correlation. Your score is 0.35, which falls into the indeterminate range.
Reference:
Please see the Machine Learning Mastery page titled How to Calculate Correlation Between Variables in Python (https://machinelearningmastery.com/how-to-use-correlation-to-understand-the-relationship-between-variables/), the Wikipedia page titled Correlation coefficient (https://en.wikipedia.org/wiki/Correlation_coefficient), and the Medium article titled What are Covariance and Correlation coefficients and their significance? (https://towardsdatascience.com/covariance-and-correlation-321fdacab168)