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2: Descriptive Statistics

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    • 2.1: Frequency and Group Frequency Distribution
      In the previous chapter, we learned about the different methods to collect data. Now, what do we do with the data? The question can be answered in this chapter.
    • 2.2: Histograms, Frequency Polygons, and Time Series Graphs
      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.
    • 2.3: Stem-and-Leaf Graphs (Stemplots), Line Graphs, and Bar Graphs
      A stem-and-leaf plot is a way to plot data and look at the distribution, where all data values within a class are visible. The advantage in a stem-and-leaf plot is that all values are listed, unlike a histogram, which gives classes of data values. A line graph is often used to represent a set of data values in which a quantity varies with time. These graphs are useful for finding trends.  A bar graph is a chart that uses either horizontal or vertical bars to show comparisons among categories.
    • 2.4: Central Tendency
      Both graphical and numerical methods of summarizing data make up the branch of statistics known as descriptive statistics. Later, descriptive statistics will be used to estimate and make inferences about population parameters using methods that are part of the branch called inferential statistics. This section introduces numerical measurements to describe sample data.
    • 2.5: Basic Concepts of Variation
      Variability describes how the data are spread out. If the data are very close to each other, then there is low variability. If the data are very spread out, then there is high variability. How do you measure variability? It would be good to have a number that measures it. This section will describe some of the different measures of variability, also known as variation.
    • 2.6: Skewness and the Mean, Median, and Mode
      Looking at the distribution of data can reveal a lot about the relationship between the mean, the median, and the mode. There are three types of distributions. A right (or positive) skewed distribution, a left (or negative) skewed distribution and a symmetrical distribution.
    • 2.7: Measures of Position
      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
    • 2.8: Descriptive Statistics Formulas
      Refer to this section when it is necessary to remember formulas for descriptive statistics.
    • 2.9: Descriptive Statistics (Exercises)
      Take some time to practice your knowledge or complete questions that your instructor has assigned.

    This page titled 2: Descriptive Statistics is shared under a CC BY-SA 1.0 license and was authored, remixed, and/or curated by Rachel Webb via source content that was edited to the style and standards of the LibreTexts platform.