Mathematicians use different statistical methods to analyze data sets. The type of analysis to best describe the data depends on the type of variables contained within the data set. Variables fall into three categories: categorical, ordinal and interval. Categorical variables have no ordering or value, but are simply descriptive categories, such as hair color or race. Ordinal variables may also be descriptive but also have a clear ordering, such as level of education or economic class. Interval variables, however, express a quantity of something with a specific value, such as annual income or temperature. Creating a statistical analysis of an interval variable allows you to analyze the quantity of something with a specific value.
Instructions
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1
Open the statistical software of your preference. Enter the quantity data into a new data file.
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2
Select the menu option to run statistical tests that compare means. Choose "One-Sample T Test" from the menu options. For example, in IBM's SPSS, you select the "Analyze" menu, then click on "Compare Means" to find "One-Sample T Test."
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Move the "Quantity" variable into the "Test Variables" field. Enter the value you wish to compare the sample against in the "Test Value" field.
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Run the one-sample T test. Record the output information such as mean, standard deviation, t score, degrees of freedom (df) and significance.