Simple Descriptive Statistics

Data Science    |    Beginner
• 10 videos | 1h 10m 1s
• Includes Assessment
Rating 4.2 of 319 users (319)
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

• Learn how to list objectives of descriptive and inferential statistics and distinguish between the two.
• 3.  Population vs. Sample
During this video, you will learn how to list objectives of population and sample and distinguish between the two.
• 4.  Probability vs. Non-Probability Sampling
In this video, learn how to list objectives of probability and non-probability sampling and distinguish between the two.
• 5.  Mean
In this video, you will learn how to define the mean of a dataset and enumerate its properties.
• 6.  Median
In this video, you will learn how to define the median and mode of a dataset and list their properties.
• 7.  Mode
During this video, you will learn how to define the range of a dataset and list its properties.
• 8.  IQR
Learn how to define the inter-quartile range of a dataset and list its properties.
• 9.  Variance
Learn how to define the variance and standard deviation of a dataset and list their properties.
• 10.  Exercise: Using Descriptive Statistics
In this video, you will learn how to differentiate between inferential and descriptive statistics, enumerate the two most important types of descriptive statistics, and define the formula for standard deviation.

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