Part 3:DATA ANALYSIS TECHNIQUES

Statistics-A Data Expert’s Recipe:

As I pondered on the next topic in this series, I felt impelled to delve into the importance of statistics within the domain of data expertise.

It’s not an attempt to intimidate, but rather an acknowledgment that a significant portion of Data Analysis principles is rooted in statistics and, by extension, mathematics.

Although, you don’t need to grasp every statistical nuance or transform into a mathematician to excel in this field, it is important to understand some basic statistical concepts.

Let’s kick things off with — the measures of central tendency:

1️⃣ Mean: The average of a set of two or more numbers.

2️⃣ Median: The middle number in a sorted list.

3️⃣ Mode: The number most frequently occurring in a set.

4️⃣ Range: The difference between the highest and lowest values.

Consider this scenario for a clearer understanding of the measure of central tendency: Imagine tracking your weekly “actual” cost of living. Most weeks, you incur a consistent expense around $100. However, in one exceptional week, an unexpected emergency arises, and you end up spending $1000.

Now, when applying the mean (average) to analyze your data, it might mislead you. The mean could give a figure that doesn’t accurately represent your regular spending pattern because it’s heavily influenced by that one outlier week with the $1000 expense as the median might be more accurate.

This is why it’s crucial to not just blindly apply statistical measures but to critically assess your data’s distribution and characteristics.

In the upcoming weeks, I’ll delve into essential “checks” and provide strategies on how to navigate such nuances in data analysis. Stay tuned for a deeper dive into the world of data analysis! 🚀 #DataAnalysis #Statistics #DataScience #LearningAnalytics