MATH 1300

This guide supports students learning to find and use statistics and data.

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Holly Surbaugh

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What is Data?

What is the difference between Data and Statistics? Data are the direct result of a survey or research. Data are raw information before any interpretation or analysis. Data are generally in a machine-readable data file. Statistics are the study of data through data analysis. Statistics can be numerical, or visual, such as a summary table or a graph.


In regular conversation, both words are often used interchangeably.

Data are raw ingredients from which statistics are created. Statistics are useful when you just need a few numbers to support an argument (ex. In 2003, 98.2% of American households had a television set--from Statistical Abstract of the United States). Statistics are usually presented in tables. Statistical analysis can be performed on data to show relationships among the variables collected. Through secondary data analysis, many different researchers can re-use the same data set for different purposes.


The What and Why of Statistics

Statistics can help provide concrete examples of a larger trend, give the basis for an important chart or graph, or make theoretical arguments tangible.

There are two main branches of statistics:

Descriptive: Concerns the numerical or quantitative data alone, and can help draw conclusions about a sample, rather than a population.

Inferential: Concerns the conclusions drawn about an entire population which are infered through the results of a random sampling of a population

Types of Data

Quantitative data/Quantitative variables: Information that can be handled numerically.

Qualitative data/Qualitative variables: Information that refers to the quality of something. Ethnographic research, participant observation, open-ended interviews, etc., may collect qualitative data. Some element of the results obtained via qualitative research may be handled numerically, eg, how many observations, number of interviews, etc.

Time series data: Any data arranged in chronological order.

Longitudinal data: Data that is collected repeatedly over a period of time, in which the same group of respondents are surveyed each time.

Discrete data: Numeric data that have a finite number of possible values.

Continuous data: Data that has an infinite number of possible values. 

Aggregate/Macro Data vs. Microdata

Aggregate or Macro Data are higher-level data that have been compiled from smaller units of data. For example, the Census data that you find on AmericanFactfinder have been aggregated to preserve the confidentiality of individual respondents. Microdata contain individual cases, usually individual people, or in the case of Census data, individual households.