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Course Details

 

Course Details

Course Code: ANLY462 Course ID: 4881 Credit Hours: 3 Level: Undergraduate

This course covers deeper elements of applied analytics techniques used to identify sources of variation causing business problems, how to design experiments to explore interactions, as well as techniques used to model relationship of business variables as well as quality control. It additionally includes applied tools to predict the future using time series analysis and seasonal forecasting. It integrates statistical analysis and visualization with applied problems. PREREQUISITE: ANLY461

Course Schedule

Registration Dates Course Dates Start Month Session Weeks
03/29/2022 - 09/02/2022 09/05/2022 - 10/30/2022 September Summer 2022 Session D 8 Week session
04/26/2022 - 09/30/2022 10/03/2022 - 11/27/2022 October Fall 2022 Session B 8 Week session
05/21/2022 - 11/04/2022 11/07/2022 - 01/01/2023 November Fall 2022 Session I 8 Week session
07/25/2022 - 12/30/2022 01/02/2023 - 02/26/2023 January Winter 2023 Session B 8 Week session

Current Syllabi

After successfully completing this course, you will be able to:

CO-1: Identify Test of hypotheses about single or two population proportions; observed set and expected frequency distributions, normal or otherwise.

CO-2: Construct a Chi-square test of hypothesis and calculate statistic for goodness of fitness and independence on a contingency table.

CO-3: Review use sign tests, Wilcoxon tests, or the Kruskal-Wallis tests of populations.

CO-4: Compute and apply seasonal indexes to make seasonally adjusted forecasts.

CO-5: Analyze the implications on the business decision-making process when given a set of descriptive statistics.

CO-6: Explain the steps and why we compute for acceptance sampling.

CO-7: Explain how to use a decision tree to analyze decision making under uncertainty and how do you it’s illustrated.

After successfully completing this course, you will be able to:

CO-1: Identify Test of hypotheses about single or two population proportions; observed set and expected frequency distributions, normal or otherwise.

CO-2: Construct a Chi-square test of hypothesis and calculate statistic for goodness of fitness and independence on a contingency table.

CO-3: Review use sign tests, Wilcoxon tests, or the Kruskal-Wallis tests of populations.

CO-4: Compute and apply seasonal indexes to make seasonally adjusted forecasts.

CO-5: Analyze the implications on the business decision-making process when given a set of descriptive statistics.

CO-6: Explain the steps and why we compute for acceptance sampling.

CO-7: Explain how to use a decision tree to analyze decision making under uncertainty and how do you it’s illustrated.

Book Title:A Practical Introduction to Index Numbers - e-book available in the APUS Online Library
ISBN:9781118977811
Publication Info:Wiley Lib
Author:Ralph, Jeff
Unit Cost:$45.00
 
Book Title:Various resources from the APUS Library & the Open Web are used. Please visit http://apus.libguides.com/er.php to locate the course eReserve.
ISBN:ERESERVE NOTE
 

Previous Syllabi

Not current for future courses.