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# What is modal class in statistics?

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According to Professor James Jones of Richland Community College, the modal class in statistics, commonly called the mode, is the raw data unit that occurs most often within a data set. This is a part of descriptive statistics, as it is the frequency of data.

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To find the single most frequent score or the most frequent group of scores in a raw data set, researchers use stem-and-leaf plots, database management programs, statistical programs or count by hand. Quantitative studies produce raw numerical data. Researchers transform information from qualitative studies into categories that researchers then count as frequencies. As a description of the data, the mode does not make inferences or predictions about the frequency of the data in a population. It provides information on the specific sample. This allows researchers to quickly assess the most common answer to a question or the most frequent choice in a study for preliminary analysis.

The other measures of central tendency include the mean and the median. The mean is the average in the data set. A simple calculation for the mean is to add all the integers and divide by the number of total integers in the sample. To find the median, or middle number, the data set must be in numerical order. Then researchers divide the total number of integers by two to find the middle position.

## Related Questions

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Experts use statistics to understand large and complex sets of data. Statistics are also helpful with surveys, which legislators use to affect policy. Knowing how statistics work is important for fully understanding news reports.

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A mathematical outlier, which is a value vastly different from the majority of data, causes a skewed or misleading distribution in certain measures of central tendency within a data set, namely the mean and range, according to About Statistics. The affected mean or range incorrectly displays a bias toward the outlier value. The median and mode values, which express other measures of central tendency, are largely unaffected by an outlier.

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When the number of classes in a histogram is increased, the data set is divided into more categories, and the histogram gives a more detailed picture of the data distribution. However, if there are too many classes, it becomes difficult to extract useful information from the histogram.