Data Exploration and Statistical Analysis of Facebook Campaigns using R

Kathleen Lara
8 min readJan 9, 2021

Most of the data exploration and predictive analysis projects I did uses python. For this article, I decided to use R to do a quick data exploration and statistical analysis of a facebook campaigns dataset available for research.

image from pixabay

Business Problem

Let’s say you’re a business and you would like to get an idea of how your social media posts and campaigns performance looks like and how you could save costs by focusing on initiatives that actually positively affects the overall success.

Some questions you might have are, how often does your team posts every week or what months do they usually post or what variables affect the interactions more.

Formulating a Hypothesis

Having good content and creative visuals is important. The management then thinks, maybe that’s enough, maybe we don’t need to do paid posts to get more visibility or interactions. You on the other hand, is pitching to allocate more budget to get more interactions. Then we formulate a hypothesis:

Ho: Paid posts means higher interactions

Ha: Paid posts does not mean having higher interactions

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Kathleen Lara

I’m a Boston based Data Scientist with a background in Data Engineering and Statistics.🤓