Chapter 1: Data & Data Preparation

What are the three steps for preforming a good statistical analysis?

1. Find the right data

2. Choose appropriate techniques for analyzing data

3. Clearly communicate information usefully and verbally

What are the key principles of data privacy?

Confidentiality, Transparency, Accountability

What are the key principles of data ethics?

Putting humans first and no biases

What is descriptive statistics?

The summary of important aspects of a data set

What is inferential statistics?

Drawing conclusions about a population based on a smaller set of data

What is cross-sectional data?

Data collected by recording a characteristic of many subjects at the same point in time

What is time-series data?

Data collected over several time periods focusing on certain groups of people, specific events, or objects

What is structured data?

Data that is predefined and can fit in a row-column format

What is unstructured data?

Data that does not conform to a predefined, row-column format

Big Data

A massive amount of both structured and unstructured data that are difficult to manage, process, and analyze using traditional data-processing tools

Categorical Variable

Labels and names

Discrete Variable

Countable number of values

Continuous Variable

Uncountable values within an interval

Nominal Scale

Represents categories and groups (order does not matter)

Ordinal Scale

Categorizes and ranks data with respect to some characteristic (order matters)

Interval Scale

Categorizes and ranks, differences are meaningful (zero does not mean “none”)

Ratio Scale

Strongest level of measurement (zero means “none”)