If you are looking to learn about statistics, but are reluctant to do so, this is the course for you. This applied training provides a solid basis for all other training courses.
- This course covers the fundamental principles and concepts in statistics for engineering applications.
- Classical and more recent exploratory data analysis techniques to efficiently visualise and summarize data are presented.
- The various uses of these methods such as outlier detection will be presented.
- Real-life engineering examples are used to illustrate the principles underlying statistical testing and decision-making in the presence of uncertainty/variation.
- Statistical hypothesis testing, risks involved when using a statistical test “alpha & beta”, p-values, confidence intervals & statistical significance are discussed.
- The principle underlying sample size and power determination will be outlined.
Course Outline
Session 1 : Descriptive Statistics
- Why do We Need Statistics in Engineering?
- Descriptive or Exploratory Data Analysis “EDA”
- Overview and Objectives
- Importance of identifying the type and role of variables in studies
- Visualization and summarizing data: the concept of distribution
- Graphical tools: histogram, Box-plot, dot-plots, raincloud plots, normal probability diagrams
- Numerical tools: mean, median, standard deviation, standard error, etc.
- Exploring the relationship between two (2) variables
- Frequency tables for categorical variables
- Pearson correlation coefficient for continuous variables
- Graphs : Scatter plots, box plots, etc.
Session 2 : Statistical inference or hypothesis testing
- Overview: What is statistical inference?
- Statistical inference with hypothesis testing:
- Null and alternative hypotheses
- One-tailed and two-tailed tests
- Test statistics: t-test, F-test, etc.
- Observed significance level or “p-value”
- Statistical significance and decision rules
- Risks of hypothesis testing
- Risks or type I and II errors
- Confidence level of a test
- Power of a Test
Session 3 : Sample Size Calculations
- The Importance of Sample Size Calculations and the Input Parameters Required to Estimate Sample Size
- Statistical Inference with Confidence Intervals: Interpretation and Use
- Statistical Inference for a Sample or a Single Group: Hypothesis Testing or Confidence Interval Approach
Duration of the Course
The recommended duration of this course is 3 online sessions.
Target Audience
This session is intended for engineers who must make decisions based on experimental data.
This session introduces important concepts in statistics and data analysis. It assumes that participants have no prior knowledge of statistics or that they have not used statistics for a long time.