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Course Description

It is often not feasible to capture parameters for an entire population; however, it’s necessary to gather statistics to estimate population parameters. In this course, you will walk through the multiple methods of collecting samples and examining margin of error and confidence intervals, including how they are calculated. You will then explore another area of inferential statistics called hypothesis testing to start with a hypothesized value. One of the most important measures to calculate is the p-value, which helps gauge the significance of your findings. You will observe the role that p-values play in hypothesis testing and the way in which they are calculated.

You are required to have completed the following courses or have equivalent experience before taking this course:

  • Presenting Quantitative Data
  • Descriptive Statistics for Business
  • Making Predictions Using Statistical Probability

Faculty Author

Cindy van Es

Benefits to the Learner

  • Examine margin of error and confidence intervals, including how they are calculated
  • Review the criteria for determining sample sizes and complete an exercise on interpreting confidence intervals
  • Explore the six steps of hypothesis testing, from developing hypotheses to stating a conclusion
  • Identify the means of testing a hypothesis and complete a sample test
  • Observe the role that p-values play in hypothesis testing and the way in which they are calculated
  • Practice computing p-values and interpreting them in Excel

Target Audience

  • Entry level to executive professionals looking to uncover insights from data
  • Students who are pre-MBA or considering earning an MBA
  • Individuals interested in moving into an analyst role
  • Individuals seeking to leverage statistical or analytic skills
  • New, emerging, and experienced leaders
  • Consultants
  • Analysts and researchers
  • Entrepreneurs

Accrediting Associations

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Cornell Dyson School
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