Minitab for Statistical Data Analysis

Minitab for Statistical Data Analysis
₹1,000₹1,500
60 mins
One-To-One Session

“Minitab transforms complex statistics into clear insights.”


What is Minitab?

Minitab is a powerful statistical software package widely used in various industries for quality improvement & data analysis. Initially developed in 1972 for teaching statistics, it has since evolved into a sophisticated tool for professionals. Minitab course offers an array of statistical tools from basic descriptive statistics to complex multivariate analyses. It is particularly popular in sectors such as manufacturing, healthcare & education where data driven decision making is crucial.


🎓Minitab for Statistical Data Analysis

🔹Introduction to Minitab interface and data handling tools

🔹Data entry, cleaning, and data organization techniques

🔹Descriptive statistics: mean, median, variance, and standard deviation

🔹Graphical analysis using histograms, boxplots, and scatter plots

🔹Probability distributions and random data generation

🔹Confidence intervals and hypothesis testing (t-test, z-test, chi-square)

🔹ANOVA for comparing multiple groups

🔹Correlation and regression analysis for relationship modeling

🔹Quality control tools: control charts and process capability analysis

🔹Interpretation of statistical output and report generation

🔹Hands-on practice with real-world datasets


🌍 Why You’ll Learn This Course

🔹To gain practical skills in statistical analysis using industry-standard software

🔹To simplify complex statistical concepts through visual and interactive tools

🔹To improve data-driven decision-making abilities

🔹To prepare for academic research, projects, and dissertations

🔹To enhance employability in data analysis, quality control, and research roles

🔹To apply statistics confidently in business, engineering, and science domains


📘 Course Outline: Minitab for Statistical Data Analysis

🔹 Module 01: Introduction to MINITAB

  1. Introduction to Minitab
  2. Overview and importance of Minitab
  3. Worksheet format and structure
  4. Data window conventions
  5. Menu bar overview

🔹 Module 02: Descriptive Statistics and Graphical Analysis

  1. Types of data
  2. Using graphs to analyze data
  3. Using statistics to analyze data

🔹 Module 03: Statistical Inference

  1. Fundamentals of statistical inference
  2. Sampling distributions
  3. Normal distribution

🔹 Module 04: Hypothesis Tests and Confidence Intervals

  1. Tests and confidence intervals
  2. One-sample t-test
  3. Two variances test
  4. Two-sample t-test
  5. Paired t-test
  6. One-proportion test
  7. Two-proportions test
  8. Chi-square test
  9. Chi-square test for association
  10. Chi-square test of independence using Minitab (Demo)

🔹 Module 05: Hypothesis Tests for Non-Normally Distributed Data

  1. Hypothesis tests for non-normal data
  2. Non-parametric tests
  3. One-sample sign test in Minitab (Demo)
  4. Two-sample Mann–Whitney U test
  5. Mann–Whitney U test in Minitab (Demo)
  6. Kruskal–Wallis test
  7. Kruskal–Wallis test in Minitab (Demo)

🔹 Module 06: Control Charts

  1. Statistical process control
  2. Control charts for variables data in subgroups
  3. Control charts for individual observations
  4. Control charts for attribute data

🔹 Module 07: Process Capability Analysis

  1. Process capability for normal data
  2. Capability indices
  3. Process capability for non-normal data

🔹 Module 08: Analysis of Variance (ANOVA)

  1. Fundamentals of ANOVA
  2. One-way ANOVA
  3. Two-way ANOVA

🔹 Module 09: Correlation and Regression

  1. Relationship between two quantitative variables
  2. Simple regression
  3. Regression analysis in Minitab
  4. Simple linear regression in Minitab (Demo)
  5. Multiple regression
  6. Multiple regression in Minitab (Demo)
  7. Interpretation and conclusions

🔹 Module 10: Measurement Systems Analysis

  1. Fundamentals of measurement systems analysis
  2. Repeatability and reproducibility
  3. Graphical analysis of a Gage R&R study
  4. Sources of variation
  5. ANOVA with a Gage R&R study
  6. Gage linearity and bias study
  7. Attribute agreement analysis

🔹 Module 11: Design of Experiments (DOE)

  1. Factorial designs
  2. Blocking and incorporation of center points
  3. Fractional factorial designs
  4. Response optimization


📊“Analyze smarter, not harder, with Minitab.”📊

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