Learning Outcomes
On completion of this course, the learner should be able to:
Demonstrate an understanding of statistical methods used in decision-making.
Demonstrate an understanding and application of statistical and mathematical models for estimation and forecasting.
Demonstrate an understanding and application of techniques used in solving optimization problems in management.
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Course Curriculum
Unit 1 - Data Collection
Unit 2 - Sampling
Unit 3 - Data Classification
Unit 4 - Measures of Location
Unit 5 - Measures of Dispersion
Unit 6 - Measures of Skewness
Unit 7 - Regression Analysis
Unit 8 - Correlation Analysis
Unit 9 - Index Numbers
Unit 10 - Network Analysis
Unit 11 - Decision Theory
Unit 12 - Forecasting
Unit 13 - Linear Programming
Unit 14 - Probability
Unit 15 - Discrete Distributions
Unit 16 - Binomial Distributions
Unit 17 - Poisson Distribution
Unit 18 - Normal Distributions
Unit 19 - Statistical Inference
Unit 20 - Estimation Theory
Unit 21 - Hypothesis Testing
Unit 22 - Non-Parametric Tests
Unit 23 - Linear Algebra & Calculus
Unit 24 - Statistical Quality Control
Target Group
The course has been designed for students undertaking Quantitative Techniques under CPA(U) professional course and has been built around the official CPA(U) syllabus. The course is also designed for students undertaking Quantitative Methods and statistics at an institution of higher learning.
Lecturer
CPA Innocent MUGISHA
CPA Innocent Mugisha is a Professor of Finance and Accounting with over 10 years experience in teaching Accounting and Finance related courses including Quantitative Techniques both at University and Professional level. His qualifications are: PhD (candidate), MBA(Finance), CPA(U), FCCA, CIPS, CTA and BCOM (Accounting). Innocent has also published various books on most topics in Accounting and Finance for Business and Professional Studies.
Pricing Plans
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