<p style="text-align:justify"><span style="font-size:14px"><span style="color:black">Data may come from a population or from a sample. Lowercase letters like </span><em><span style="color:black">x </span></em><span style="color:black">or </span><em><span style="color:black">y </span></em><span style="color:black">generally are used to represent data values. Most data can be put into the following categories:</span></span></p>

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<p><span style="font-size:14px"><span style="color:black">&bull; Qualitative</span></span></p>

<p><span style="font-size:14px"><span style="color:black">&bull; Quantitative</span></span></p>

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<p style="text-align:justify"><span style="font-size:14px"><strong><span style="color:black">Qualitative data </span></strong><span style="color:black">are the result of categorizing or describing attributes of a population. Qualitative data are also often called </span><strong><span style="color:black">categorical data</span></strong><span style="color:black">. Hair color, blood type, ethnic group, the car a person drives, and the street a person lives on are examples of qualitative data. Qualitative data are generally described by words or letters. For instance, hair color might be black, dark brown, light brown, blonde, gray, or red. Blood type might be AB+, O&ndash;, or B+. Researchers often prefer to use quantitative data over qualitative data because it lends itself more easily to mathematical analysis. For example, it does not make sense to find an average hair color or blood type.</span></span></p>

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<p style="text-align:justify"><span style="font-size:14px"><strong><span style="color:black">Quantitative data </span></strong><span style="color:black">are always numbers. Quantitative data are the result of </span><strong><span style="color:black">counting </span></strong><span style="color:black">or </span><strong><span style="color:black">measuring </span></strong><span style="color:black">attributes of a population.Amount of money, pulse rate, weight, number of people living in your town, and number of students who take statistics are examples of quantitative data. Quantitative data may be either </span><strong><span style="color:black">discrete </span></strong><span style="color:black">or </span><strong><span style="color:black">continuous</span></strong><span style="color:black">.</span></span></p>

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<p style="text-align:justify"><span style="font-size:14px"><span style="color:black">All data that are the result of counting are called </span><strong><span style="color:black">quantitative discrete data</span></strong><span style="color:black">. These data take on only certain numerical values. If you count the number of phone calls you receive for each day of the week, you might get values such as zero, one, two, or three.</span></span></p>

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<p style="text-align:justify"><span style="font-size:14px"><span style="color:black">Data that are not only made up of counting numbers, but that may include fractions, decimals, or irrational numbers, are called </span><strong><span style="color:black">quantitative continuous data</span></strong><span style="color:black">. Continuous data are often the results of measurements like lengths, weights, or times.</span></span></p>

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<p style="text-align:justify"><span style="font-size:14px"><span style="color:black">A list of the lengths in minutes for all the phone calls that you make in a week, with numbers like 2.4, 7.5, or 11.0, would be quantitative continuous data.</span></span></p>