Implementing Scientific Decision Making

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Course Description PDF

Course Focus

Summary statistics are one way to forecast uncertain outcomes, and the statistical results can be used to make decisions or guide strategy. Since summary statistics are based on a data sample, they typically inform intuitive decision-making. That is, the model requires interpretation which relies on the business intuition of the person using it.

In this course you will learn how to examine sample data scientifically to limit any generalizations to only the patterns that have the strongest statistical support. As always, intuition and business knowledge play an important role in the process, but this course will prepare you to apply a level of scientific rigor that will lead to better results.

Who Should Take this Course?

This course is appropriate for anyone from analyst to the SVP with no background in statistics. It is designed for individuals who need to perform analysis to support decision making. The course content draws on examples across all business types.

Key Benefits

Participants who complete this course will be able to...

  • Formulate a question as a null and alternate hypothesis
  • Calculate a test statistic from sample data
  • Identify the statistical test most appropriate for testing your hypothesis
  • Determine the likelihood of finding a result at least as extreme as the test statistic assuming the null hypothesis

Topics Include

Module 1: Define a Hypothesis

Module 2: Test the Hypothesis

Module 3: Testing and Conclusions

Faculty

Course Cost US$1380
Hours to Complete Course: 9
CEUS earned 0.6
This course is part of one or more online certificates:

Please choose from the following course start dates:

27 June 2018
18 July 2018
08 August 2018
29 August 2018
19 September 2018
10 October 2018
31 October 2018
21 November 2018
12 December 2018
02 January 2019
23 January 2019
13 February 2019
06 March 2019
27 March 2019
17 April 2019
08 May 2019
29 May 2019
19 June 2019
10 July 2019
31 July 2019
21 August 2019
11 September 2019
02 October 2019
23 October 2019
13 November 2019
04 December 2019
25 December 2019
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