Simple Descriptive Statistics

Data Science    |    Beginner
  • 10 Videos | 1h 10m 1s
  • Includes Assessment
  • Earns a Badge
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Along the career path to Data Science, a fundamental understanding of statistics and modeling is required. The goal of all modeling is generalizing as well as possible from a sample to the population of big data as a whole. In this 10-video Skillsoft Aspire course, learners explore the first step in this process. Key concepts covered here include the objectives of descriptive and inferential statistics, and distinguishing between the two; objectives of population and sample, and distinguishing between the two; and objectives of probability and non-probability sampling and distinguishing between them. Learn to define the average of a data set and its properties; the median and mode of a data set and their properties; and the range of a data set and its properties. Then study the inter-quartile range of a data set and its properties; the variance and standard deviation of a data set and their properties; and how to differentiate between inferential and descriptive statistics, the two most important types of descriptive statistics, and the formula for standard deviation.

WHAT YOU WILL LEARN

  • enumerate objectives of descriptive and inferential statistics and distinguish between the two
    enumerate objectives of population and sample and distinguish between the two
    enumerate objectives of probability and non-probability sampling and distinguish between the two
    define the mean of a dataset and enumerate its properties
    define the median and mode of a dataset and enumerate their properties
  • define the range of a dataset and enumerate its properties
    define the inter-quartile range of a dataset and enumerate its properties
    define the variance and standard deviation of a dataset and enumerate their properties
    differentiate between inferential and descriptive statistics, enumerate the two most important types of descriptive statistics, and define the formula for standard deviation

IN THIS COURSE

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