Principles of Analysis : Descriptive and Inferential Statistics

PRINCIPLES OF ANALYSIS: DESCRIPTIVE AND INFERENTIAL STATISTICS

INTRODUCTION

Effective data analysis is essential for decision-making, reporting, and quality control in any professional environment. Understanding descriptive and inferential statistics helps individuals summarize data, identify trends, and make informed predictions based on statistical evidence.

This Principles of Analysis session provides a high-level introduction to essential statistical concepts, including data measurement, summary statistics, inferential techniques, and data quality considerations. The session is delivered in a discussion-based format, with no group activities, offering an overview before more detailed sessions on specialized topics.

This John Varlow | Training and Consultancy session will cover:

✔ Understanding levels of measurement, central tendency, and dispersion
✔ Exploring prevalence and incidence rates in data reporting
✔ Effective data presentation and visualization methods
✔ Introduction to inferential statistics, statistical tests, P-values, and confidence limits
✔ The importance of data quality in statistical analysis
✔ Basic principles of statistical process control (SPC)

SESSION OBJECTIVES

By the end of this 3-hour session, participants will be able to:

✔ Understand descriptive statistics and their role in data analysis
✔ Recognize key statistical measures such as mean, median, variance, and standard deviation
✔ Differentiate between prevalence and incidence rates and their significance in data analysis
✔ Apply best practices for data presentation and visualization
✔ Gain a foundational understanding of inferential statistics and hypothesis testing
✔ Appreciate the importance of data quality and its impact on decision-making
✔ Be introduced to statistical process control (SPC) techniques

TRAINING METHODOLOGY

This session is interactive and discussion-based, designed to provide a clear conceptual foundation in statistical analysis. Unlike other workshops, there are no group activities—instead, the focus is on theoretical understanding, real-world applications, and structured discussions.

✔ Clear explanations of fundamental statistical concepts
✔ Real-world examples to illustrate data analysis in practice
✔ Opportunities for discussion and Q&A to reinforce learning
✔ Preview of more advanced statistical topics covered in future sessions

This approach ensures that participants gain a solid statistical foundation while preparing them for more detailed sessions on specific analysis techniques.

WHO SHOULD ATTEND?

This session is designed for professionals who work with data, reports, or decision-making and need a strong introduction to statistical concepts. It is particularly beneficial for:

✔ Managers & Analysts who need a foundational understanding of statistics
✔ Professionals handling reports, data summaries, or performance tracking
✔ Quality Control & Process Improvement Teams
✔ Finance, Risk, and Operations Specialists
✔ Anyone seeking to improve their ability to interpret numerical data

Pre-requisites:

✔ Basic numeracy skills are required, but no prior statistical knowledge is necessary.

SESSION CONTENT

1. Introduction to Descriptive Statistics

✔ Understanding levels of measurement (Nominal, Ordinal, Interval, Ratio)
✔ Measures of central tendency: Mean, Median, Mode
✔ Measures of dispersion: Range, Variance, Standard Deviation

2. Understanding Rates in Data Analysis

✔ The concept of rates in statistics
✔ Prevalence vs. Incidence – key differences and applications

3. Data Presentation & Visualization

✔ Selecting the right graph or chart for different data types
✔ Common errors in data visualization and how to avoid them
✔ Best practices for clear and effective data presentation

4. Introduction to Inferential Statistics

✔ Understanding statistical significance and uncertainty
✔ What are P-values and confidence limits, and how do they impact decisions?
✔ Basic statistical tests for two groups (e.g., t-tests)

5. Importance of Data Quality

✔ The impact of errors, biases, and missing data on analysis
✔ Ensuring data accuracy and integrity in reporting

6. Introduction to Statistical Process Control (SPC)

✔ The role of SPC in monitoring and improving processes
✔ An introduction to control charts and their applications

DURATION

3 Hours

This session provides a concise yet comprehensive introduction to key statistical concepts, making it an excellent starting point for those looking to build confidence in data analysis and interpretation.

CERTIFICATION

Upon successful completion of this session, participants will receive a John Varlow | Training and Consultancy Certificate of Completion.

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