Minitab Essentials Course Overview

Minitab Essentials Course Overview

The Minitab Essentials course is designed to provide learners with comprehensive online training in utilizing Minitab, a statistical software package. This course equips participants with the foundational skills necessary to perform data analysis and solve business problems effectively. Through Minitab training, learners can understand how to import and format data, create various charts such as bar charts, histograms, and boxplots, and use statistical tools like Pareto charts and scatterplots.

Each module focuses on a specific topic, starting from basics like data handling to more complex analyses including t-tests, proportion tests, and ANOVA. The course also delves into understanding relationships between variables using scatterplots, correlation, and regression analysis, ensuring that participants can make data-driven decisions.

By mastering these skills, learners will be prepared to contribute to quality improvement initiatives and business analytics projects. Minitab online training is essential for professionals seeking to enhance their proficiency in statistical analysis and data interpretation through practical, hands-on experience with Minitab training.

This is a Rare Course and it can be take up to 3 weeks to arrange the training.

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  • Live Online Training (Duration : 16 Hours)
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  • Live Online Training (Duration : 16 Hours)
  • Per Participant

♱ Excluding VAT/GST

Classroom Training price is on request

You can request classroom training in any city on any date by Requesting More Information

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Course Prerequisites

Certainly! To ensure that participants are well-prepared and can derive maximum benefit from the Minitab Essentials course, the following are the minimum prerequisites:

  • Basic understanding of statistics: Familiarity with foundational statistical concepts such as mean, median, standard deviation, and basic probability will be helpful.
  • General computer literacy: Comfort with operating a computer, managing files, and navigating software interfaces.
  • Knowledge of Microsoft Excel: Since Minitab interacts well with spreadsheet software, understanding how to work with Excel for data entry and manipulation can be beneficial.
  • Analytical thinking: An aptitude for analyzing data and a keen interest in drawing insights from data sets will enhance the learning experience.
  • English proficiency: Ability to understand and communicate in English, as the course materials and instruction are typically provided in English.

No prior experience with Minitab software is required, as the course will cover the essentials from the ground up.

Target Audience for Minitab Essentials

  1. The Minitab Essentials course is designed for professionals seeking to master statistical analysis and process improvement using Minitab software.

  2. Target audience for the Minitab Essentials course:

  • Quality Assurance Engineers
  • Data Analysts
  • Process Improvement Specialists
  • Six Sigma Green and Black Belts
  • Research Scientists
  • Production Managers
  • Business Analysts
  • Statisticians
  • Manufacturing Engineers
  • Product Development Professionals
  • Quality Control Technicians
  • Lean Practitioners
  • Operations Analysts
  • Project Managers involved in data-driven decision-making
  • Supply Chain Analysts
  • Academic Researchers and Graduate Students in statistics or related fields

Learning Objectives - What you will Learn in this Minitab Essentials?

Introduction to Course Learning Outcomes and Concepts

The Minitab Essentials course equips learners with foundational skills in statistical analysis and data interpretation using Minitab software, covering data visualization, inferential statistics, and hypothesis testing.

Learning Objectives and Outcomes

  • Understand how to import and format datasets effectively within Minitab for accurate analysis.
  • Create and interpret Bar Charts to visualize categorical data and identify patterns.
  • Generate Histograms to analyze and display the distribution of continuous data sets.
  • Utilize Boxplots for comparing distributions and identifying outliers in data sets.
  • Construct and interpret Pareto Charts to prioritize problem areas or identify the most significant factors in a dataset.
  • Create Scatterplots to examine relationships between two continuous variables and identify potential correlations.
  • Perform and interpret Chi-Square Analysis to test relationships between categorical variables using contingency tables.
  • Calculate and understand Measures of Location (mean, median, mode) and Variation (range, variance, standard deviation) in data sets.
  • Conduct and interpret t-Tests to compare means and assess statistical significance in the differences observed.
  • Execute Proportion Tests to analyze categorical data and compare sample proportions to a hypothesized value.
  • Test for Equal Variance to verify assumptions for parametric tests or to compare the variability between groups.
  • Determine Power and Sample Size to design experiments with adequate power to detect meaningful effects.
  • Evaluate Correlation coefficients to measure the strength and direction of linear relationships between variables.
  • Apply Simple Linear and Multiple Regression techniques to model relationships between variables and make predictions.
  • Perform One-Way ANOVA to test for significant differences between means across multiple groups.
  • Conduct Multi-Variable ANOVA to understand the effects of two or more categorical independent variables on a continuous dependent variable.

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