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Mathematics LibreTexts

4: Descriptive Statistics

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  • 4.1: Introduction to Statistics
    The mathematical theory of statistics is easier to learn when you know the language. This module presents important terms that will be used throughout the text.
  • 4.2: Collecting Data
    Data are individual items of information that come from a population or sample. Data may be classified as qualitative, quantitative continuous, or quantitative discrete. Because it is not practical to measure the entire population in a study, researchers use samples to represent the population. A random sample is a representative group from the population chosen by using a method that gives each individual in the population an equal chance of being included in the sample.
  • 4.3: Visual Summaries of Data
    Some calculations generate numbers that are artificially precise. It is not necessary to report a value to eight decimal places when the measures that generated that value were only accurate to the nearest tenth. Round off your final answer to one more decimal place than was present in the original data. This means that if you have data measured to the nearest tenth of a unit, report the final statistic to the nearest hundredth.
  • 4.4: Other Summaries
    A histogram is a graphic version of a frequency distribution. The graph consists of bars of equal width drawn adjacent to each other. The horizontal scale represents classes of quantitative data values and the vertical scale represents frequencies. The heights of the bars correspond to frequency values. Histograms are typically used for large, continuous, quantitative data sets. A frequency polygon can also be used when graphing large data sets with data points that repeat.
  • 4.5: Measures of the Center and Variation of the Data
    The mean and the median can be calculated to help you find the "center" of a data set. The mean is the best estimate for the actual data set, but the median is the best measurement when a data set contains several outliers or extreme values. The mode will tell you the most frequently occurring datum (or data) in your data set. The mean, median, and mode are extremely helpful when you need to analyze your data.
  • 4.6: Measures of the Location of the Data and Outliers
    The values that divide a rank-ordered set of data into 100 equal parts are called percentiles and are used to compare and interpret data. For example, an observation at the 50th percentile would be greater than 50 % of the other obeservations in the set. Quartiles divide data into quarters. The first quartile is the 25th percentile, the second quartile is 50th percentile, and the third quartile is the the 75th percentile. The interquartile range is the range of the middle 50 % of the data values


4: Descriptive Statistics is shared under a not declared license and was authored, remixed, and/or curated by LibreTexts.

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