Day 1 of 66 Days of Data Science

For the 66 days of data science challenge, I am going back to the basics and relearning statistics. I am using a textbook titled Introduction to The Practice of Statistics Sixth Edition — Moore, McCabe Craig. Here is what I learned so far.

Data are numbers with context. Before you do any statistical calculation and create data visualizations you need to start with the habit of forming a question. “What does the data tell me?”

The starting point to any statistical analysis is to master the art of examining data.

|Person | Age | Weight
| — -| — -| — -| — -| — -|
|Buttercup| 24 |110|
|Bubbles| 24 |105|
|Blossom| 24 |107|

This is a table that contains data.

Individuals also known as cases, observations, and rows. If you are into programming you can think of rows as objects. Each object is like a noun that describes a (person, place, or thing). Objects have characteristics called variables.

Variables are also known as columns.

When you plan to do an exploratory data analysis(EDA) ask yourself the following questions.

  1. Why? Is there a specific question that I want to be answered by looking at this data? What is the purpose of this data?
  2. Who? What population does this data describe?
  3. What? How many columns does this data set have? How are these variables defined?

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