Inferential Statistics

Data Science    |    Beginner
  • 10 Videos | 1h 5m 30s
  • Includes Assessment
  • Earns a Badge
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In this Skillsoft Aspire course on data science, learners can explore hypothesis testing, which finds wide applications in data science. This beginner-level, 10-video course builds upon previous coursework by introducing simple inferential statistics, called the backbone of data science, because they seek to posit and prove or disprove relationships within data. You will start by learning steps in simple hypothesis testing: the null and alternative hypotheses, s-statistic, and p-value, as ach term is introduced and explained. Next, listen to an informative discussion of a specific family of hypothesis tests, the t-test. Then learn to describe their applications, and become familiar with how to use cases including linear regression. Learn about Gaussian distribution and the related concepts of correlation, which measures relationships between any two variables, and autocorrelation, a special form used in the concept of time-series analysis. In the closing exercise, review your knowledge by differentiating between the null and the alternative hypotheses in a hypothesis testing procedure, then enumerating four distinct uses for different types of t-tests.

WHAT YOU WILL LEARN

  • draw the shape of a Gaussian distribution and enumerate its defining properties
    enumerate the steps involved in hypothesis testing and define the null and alternative hypotheses
    describe the role of test statistic and p-value in accepting or rejecting a null hypothesis
    enumerate types and uses of t-tests in hypothesis testing
    outline the significance of skewness and kurtosis and define the skewness and kurtosis of a normally distributed random variable
  • calculate the autocorrelation of a time series
    define linear regression
    interpret the R-squared of a regression and identify overfitting
    differentiate between null and alternative hypotheses, enumerate four use cases for t-tests, and calculate the correlation of time series with itself

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    2m 54s
    UP NEXT
  • Playable
    2. 
    Gaussian Distribution
    6m 48s
  • Locked
    3. 
    Inferential Statistics and Hypothesis Testing
    5m 44s
  • Locked
    4. 
    Simplified Example of Hypothesis Testing
    4m 9s
  • Locked
    5. 
    T-tests
    9m
  • Locked
    6. 
    Skewness and Kurtosis
    4m 15s
  • Locked
    7. 
    Correlation and Autocorrelation
    5m 17s
  • Locked
    8. 
    Introducing Linear Regression
    8m 45s
  • Locked
    9. 
    Overfitting and Goodness-of-Fit
    8m 56s
  • Locked
    10. 
    Exercise: Basic Inferential Statistics
    5m 41s

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