Basic Statistics using Minitab
The Basics Statistics and Tool IMinitab course offered by NPDD House is designed to provide participants with a comprehensive understanding of fundamental statistical concepts and practical application using the powerful statistical software, IMinitab. This course serves as an excellent introduction to statistics for individuals who are new to the field or those seeking to refresh their knowledge.
Throughout the duration of this course, participants will delve into the core principles of statistics and gain hands-on experience in using IMinitab, a widely used software tool for statistical analysis and data visualization. The course combines theoretical concepts with practical examples and exercises, enabling participants to grasp statistical concepts and apply them effectively.
Scope
The Basics Statistics and Tool IMinitab course offers a comprehensive curriculum covering statistical concepts, data analysis, and practical skills in utilizing IMinitab for informed decision-making.
Module 1: Introduction to Statistics
In this module, participants will be introduced to the field of statistics and its wide-ranging applications. They will explore descriptive statistics, which involves measures of central tendency and variability to summarize data. Participants will also learn about probability and probability distributions, as well as different sampling techniques and sampling distributions. The module will conclude with an overview of inferential statistics, which involves drawing conclusions and making inferences about populations based on sample data.
Module 2: Data Visualization
This module focuses on the visual representation of data. Participants will learn how to create various types of graphs, including histograms, box plots, and scatter plots, to visually represent data sets. They will understand how to interpret these graphical representations to gain insights into data patterns, trends, and relationships. Effective data visualization is crucial for understanding and communicating complex data sets, and participants will gain practical skills in creating and interpreting visualizations.
Module 3: Hypothesis Testing
Hypothesis testing is a fundamental aspect of statistical analysis. In this module, participants will learn how to formulate null and alternative hypotheses for different scenarios. They will explore various hypothesis tests, including one-sample and two-sample tests, and understand how to select appropriate test statistics. Participants will also learn how to interpret p-values, make decisions based on hypothesis testing results, and consider the potential for Type I and Type II errors.
Module 4: Regression Analysis
Regression analysis is a powerful statistical technique used to model relationships between variables. In this module, participants will gain an understanding of simple linear regression and multiple linear regression. They will learn how to interpret regression coefficients, assess model fit, and use regression models for making predictions. Participants will also become familiar with diagnostic tools to evaluate the assumptions and performance of regression models.
Module 5: Design of Experiments (DOE)
Design of Experiments (DOE) is a systematic approach to optimizing processes and improving product quality. In this module, participants will learn how to plan and conduct designed experiments. They will explore the analysis of variance (ANOVA) technique for DOE and understand how to interpret DOE results to identify critical process factors and optimize performance. Participants will gain practical skills in applying DOE principles to real-world scenarios.
Module 6: Statistical Process Control (SPC)
Statistical Process Control (SPC) is a methodology for monitoring and controlling processes to ensure quality standards. This module will cover the principles of SPC and its applications. Participants will learn how to create control charts to monitor process performance, analyze process capability, and identify and address variations. They will understand the importance of maintaining stable and predictable processes for consistent quality outcomes.
Module 7: Quality Improvement Techniques
This module focuses on various statistical tools and techniques used for quality improvement. Participants will learn how to use Pareto charts to prioritize problems, fishbone diagrams for root cause analysis, and the 5 Whys technique for problem-solving. They will gain practical skills in applying these quality improvement methodologies to identify and address issues that impact product or process quality.
Module 8: Hands-on Practice with IMinitab
Throughout the course, participants will engage in hands-on exercises using IMinitab, a popular statistical software package. In this module, they will gain practical experience in using IMinitab to import and analyze data, perform statistical analyses, and interpret the output and results. Participants will strengthen their proficiency in utilizing IMinitab as a powerful tool for data analysis and statistical modeling.
By completing this course, participants will gain a solid foundation in statistics, data visualization, hypothesis testing, regression analysis, DOE, SPC, quality improvement techniques, and hands-on experience with IMinitab.
Who will benefit from this course?
- Students pursuing degrees in fields such as statistics, mathematics, data science, or related disciplines, who want to develop a strong foundation in statistical analysis and data-driven decision-making.
- Researchers and analysts who deal with data on a regular basis and seek to enhance their analytical skills to effectively analyze and interpret data sets.
- Professionals working in industries such as finance, marketing, healthcare, manufacturing, quality control, and operations, who need to make data-driven decisions and optimize processes for improved outcomes.
- Quality assurance and process improvement specialists who want to deepen their understanding of statistical techniques and tools to enhance product quality, identify process variations, and implement effective solutions.
- Individuals seeking to enhance their resume and career prospects by adding valuable statistical and data analysis skills, making them desirable candidates for a wide range of job roles that require data-driven decision-making abilities.
Join the Basics Statistics and Tool IMinitab course at NPDD House to acquire the statistical knowledge and practical skills necessary to excel in academic, research, and professional domains where data analysis and statistics play a crucial role.