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Q:

# What are the components of a statistical table?

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A statistical table contains several components designed to illustrate the data, including a title for the table, the table number, the heading and subheadings, the table body, the table spanner, dividers and table notes. Tables are used to display data obtained from an experiment and are often included in lab reports or research papers and presentations.

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The title of the table provides a description of the contents. It may include the groups, their classifications and the variables. The title should never be more than one or two lines. Table numbers are needed to refer to a specific set of values being discussed. This is especially useful if there are multiple tables.

Headings and subheadings identify and establish the order of the data. Column headings and column spanners are included in headings and subheadings. The table body is where the bulk or meat of the data is located. This includes any means, percentages, frequencies or other values found that are significant. Table spanners divide data in a table without the addition of another column. Dividers are horizontal lines that separate different parts of the table. Finally, table notes explain any information that is included in the table, including definitions and abbreviations.

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## Related Questions

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Advanced Placement, or AP, Statistics is an accelerated high school course involving the collection, analysis and interpretation of mathematical data. This non-calculus-based course challenges students to develop theories and draw conclusions by identifying trends and divergences in data patterns. The curriculum typically requires students to design mock studies and surveys.

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A trend in mathematics is a pattern in a set of data points. Knowing the trend allows outcomes to be predicted by a mathematical model. Estimating the trend of data requires a technique known as regression or curve fitting.

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Variance measures how the data in a given variable distribution are spread relative to the mean. Operationally, it is the average squared distance from the mean and is calculated by the square root of the standard deviation. Conceptually, it indicates how much variation is within a given sample.