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Statistics, Data, Graphs, and Other Factual Support: Using These Statistics

Statistics and data help back up a claim you make in a research or persuasive paper. Find more statistics in the reference section of the library.

Interpreting Data

How to Interpret Data

(and Not Get Fooled by Misleading Numbers)

Data can be really useful when figuring out the facts about what is happening and how big the influence is. The problem is that there are a lot of individuals and organizations that would gain from persuading people by using misleading layouts of information. 

How can Numbers Be Misleading? 

Good things to check are:

  • focuses on one population and does not compare it to the overall population
  • zooms in on one tiny change and makes it look like a big change
  • the visuals on the graph are greatly exaggerated even though it doesn't match the numbers
  • units of measurement can be one person or one hundred thousand people; always check the small print

About Data and Statistics

What is Data?

When an organization, government, university, company, or individual collects information and organizes it in order to determine patterns. When making a persuasive statement, it is helpful to have data or statistics because they can be cited and used to support your claim.

Quantitative Data: 

When presenting a set of numbers, a graph, or percentages in numeric format, that data is considered quantitative. This kind of data is difficult to disagree with since numbers are not based on opinions or feelings.

Qualitative Data:

This kind of data is often in the form of a short answer or paragraph. Qualitative data can be an anecdote or a story that is weighed to prove one side or another. While qualitative data is important and should not be ignored, this kind of data shouldn't be considered factual.

Books on Big Data

Weapons of Math Destruction

Weapons of Math Destruction

We live in the age of the algorithm. Increasingly, the decisions that affect our lives -- where we go to school, whether we get a car loan, how much we pay for health insurance -- are being made not by humans, but by mathematical models. In theory, this should lead to greater fairness: Everyone is judged according to the same rules, and bias is eliminated. But as Cathy O'Neil reveals in this book, the opposite is true. The models being used today are opaque, unregulated, and uncontestable, even when they're wrong

Big Data, Big Analytics

The availability of Big Data, low-cost commodity hardware and new information management and analytics software has produced a unique moment in the history of business. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. These capabilities are neither theoretical nor trivial. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue and profitability. The Age of Big Data is here, and these are truly revolutionary times.

Big Data

Explores the idea of big data, which refers to our newfound ability to crunch vast amounts of information, analyze it instantly, and draw profound and surprising conclusions from it.

Transforming Business

Based on the findings of an extensive research project that surveyed more than 5,500 enterprise employees and functional decision makers across the United States and China, Transforming Business: Big Data, Mobility and Globalization explores the influence of technology in the workplace and the implications to company culture, functional responsibilities and competitive advantage.

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