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Data Analysis for Internal Auditors

Course Description

Print-friendly Course Description and Outline

Executing a cost-effective and value-added audit requires an understanding of population analysis. Without this knowledge, you run the risk of spreading your resources and your sampling over low risk subsets of the population. This could result in crucial data not being collected.

In this course, you will learn when and how to use population analysis in the planning phase of the audit and how to identify subsets of the population that behave differently from a benchmark data set. This course will also teach you how to prepare for the conduct phase of the audit by understanding how to use random sampling and non-random selection.

This course is appropriate for auditors, managers, and executives working in both the public and private sectors.

Course Objectives

  • Summarize introductory terminology and methodology related to Data Analysis.
  • Evaluate shapes of distribution relevant to their important characteristics.
  • Determine which measure of central tendency and variation to use based on the frequency distribution.
  • Evaluate the important differences between a set of data and a chosen benchmark standard using shape, central tendency, and variation.
  • Determine when to use correlation and time series analysis.
  • Employ random sampling techniques (simple and stratified sampling).
  • Understand why haphazard sampling should not be used.
  • Identify the criteria for non-random selection techniques.
Course Duration: 1 day(s)
CPE Hours Available: 8
Knowledge Level: Intermediate
Field of Study: Statistics
Advance Preparation: 
Delivery Format: eLearning (Group-Internet-Based); On-site Training (Group-Live); Seminar (Group-Live)

​Introduction to Data Analysis

  • Defining Data Analysis
  • Data Analysis and Audit Planning
  • Population
  • Random Sample
  • Variables

Population Analysis: Shapes of Frequency Distributions

  • Descriptive Statistics
  • Graphical Presentation
    • Uniform Distribution
    • Skewed Distribution
    • Bimodal Distribution
    • Normal Distribution

Population Analysis: Measures of Central Tendency and Variation

  • Measures of Central Tendency
    • Mode
    • Median
    • Mean
  • Shape of Distribution and Central Tendency
    • Measures of Variability
    • Range
    • Quartile Deviation
    • Standard Deviation

Population Analysis: Comparison to Benchmarks

  • IPPF Standard 2320 – Practice Advisory 2320-1 Benchmarking
  • Recalculations
  • Non-Random Selection

Case Study Using Frequency Distributions

Population Analytics: Time Series and Correlational Analysis

  • Time Series Analysis
  • Case Study Using Time Series Analysis
  • Correlational Analysis
  • Case Study Using Correlations

Random Sampling

  • The Randomness Assumption
  • Types of Random Sampling
    • Simple Random Sampling
    • Stratified Random Sampling
    • Haphazard Sampling

Non-Random Selection

  • Defining Non-Random Selection
  • Fraud Red Flags
  • How to Perform Non-Random Selection
  • The Credibility Obstacle
  • Case Study Using Non-Random Selection

​Most courses can be delivered through on-site training. You might be surprised that the organization leading the profession is just as committed to the delivery of affordable training.

Contact us by calling +1-407-937-1388 or send an e-mail to


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