Statistics for Decision Making – Self Paced

Categories: Self Paced
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About Course

This online course covers the use of statistics for decision making. It is designed to provide students with the necessary skills to analyze and interpret data in order to make informed decisions. Topics covered in this course include descriptive statistics, probability distributions, hypothesis testing, correlation and regression, and decision analysis. The course begins with a discussion of the importance of statistics in decision making and introduces students to the fundamental concepts and techniques used in statistical data analysis. Students will learn how to use descriptive statistics to summarize data, calculate probabilities, and use hypothesis testing to make inferences. They will also learn how to use correlation and regression analysis to analyze relationships between variables and how to use decision analysis to make optimal decisions. In addition, the course provides an introduction to the use of software to analyze data. Students will learn how to use Excel to perform statistical computations and visualize data.  By the end of the course, students should be able to: • Understand the importance of statistics for decision making • Summarize data using descriptive statistics • Calculate probabilities using probability distributions • Use hypothesis testing to make inferences • Analyze relationships between variables using correlation and regression • Use decision analysis to make optimal decisions •

This course is designed for students with a basic understanding of statistics, but no prior knowledge of the topics covered is required. This course is also suitable for business and non-business students who are interested in improving their decision making skills.

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What Will You Learn?

  • Fundamentals of Statistics
  • Population and Sample
  • Hypothesis Testing
  • ANOVA One Way
  • ANOVA Two Way
  • Simple Linear Regression
  • Dimensionality Reduction
  • Principal Component Analysis

Course Content

Self Paced Content

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