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Statistics for Data Analytics

Statistics can be used to draw conclusions about data and provides a foundation for more sophisticated data analysis techniques. Viewing questions about data from a statistical perspective allows data scientists to create more predictable algorithms to convert data effectively into knowledge. As such, it is essential for data analysts to have a strong understanding of both descriptive and inferential statistics.

In this course, students will gain a comprehensive introduction to the statistical theories and techniques necessary for successful data mining and analysis. Particular attention will be paid to topics critical to data analytics, such as descriptive and inferential statistics, probability, linear and multiple regression, hypothesis testing, Bayes Theorem, and principal component analysis. This course prepares students for subsequent Data Mining courses.

Course Highlights:

  • Descriptive statistics
  • Two variable relationships
  • Probability
  • Bayes Theorem
  • Probability distributions
  • Sampling distributions
  • Confidence intervals
  • One- and two-sample hypothesis testing
  • Categorical data
  • Least-squares regression inference
  • Principal component analysis (PCA)

Course Learning Outcomes:

  • Organize, summarize, and present data
  • Describe the relation between two variables
  • Work with sample data to make inferences about the data
  • Gain an understanding of linear algebra

Required Software: Students will use MyStatLab and StatCrunch to complete assignments in this course. The instrutor will provide students with student links to purchase student versioins of this software on the first day of class.

Required Textbook: On the first day of class, the instructor will provide students with the information needed to purchase the required eBook which will include access to the above software.

Course typically offered: Online in every quarter.

Prerequisites: None

Next steps: Upon completion of this course, considering taking Fundamentals of Data Science to continue learning.

More Information: For more information about this course, please contact

Course Number: CSE-41264
Credit: 3.00 unit(s)
Related Certificate Programs: 

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