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Data and Statistics

What is data?

Data include sets of raw numbers, usually with many variables, and with the capability of being manipulated.

Think about the census as data about numbers of people in a geographic region. Variables will include such things as male vs female, age, income levels, racial/ethnic background, education, etc. You can manipulate the numbers to answer questions about the data -- for example, does income level correlate with education? Raw data is just numbers – no correlations, no comparisons.

When to use which

Use data … if you need to do in-depth analysis for research

  • If you want to make a correlation between aggressive behavior and gender and video games, you may need to find data and establish your own correlation.
  • If you want to make a point that too much government money is spent on moon exploration, you may need to find data to compare money spent on social issues vs. moon exploration

Use statistics … if you need quick facts to make a point.

  • If your point is that more males than females report bringing weapons onto campus, you can find statistics to support your argument.
  • If you're arguing that the price of textbooks has been rising, you can find statistics to prove it.

What are statistics?

Statistics are data that has been analyzed in some way – percentages, graphs, charts – also called “statistical data.”

Statistics are usually presented in graphs or charts so you can visualize the data connections.

Read the description to find out what the chart and numbers are all about. Where would you go for the raw data? Always look at the source. If you found statistics from the US National Center for Education Statistics, would you trust it? Probably. But you should always evaluate the source.

Bias in Statistics

Statistics can be used to make whatever point you want. For example, the statistics Planned Parenthood reports about abortion may be different from those used by the National Right to Life organization. Two groups can take the same data and present it to fit their needs. Always be alert for bias in statistics!

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