Duration
2 days
Overview
In this 2-days foundation course, you will learn to decrease the time required for statistical analysis by quickly learning how to navigate Minitab’s user-friendly and customizable environment. Learn how to easily import data and export output. Develop sound statistical approaches to data analysis by learning how to create and interpret a wide variety of graphs. Augment your graphical analysis by learning the foundation for important statistical concepts such as hypothesis testing and confidence intervals. By analyzing a variety of real world data sets, learn how to match the appropriate statistical tools to your own applications and how to correctly interpret statistical output to reveal problems with a process or to show evidence of an improvement. Learn how to explore your processes through statistical modeling tools that help to uncover and describe relationships between variables. A strong emphasis is placed on making good business decisions based upon the practical application of statistical techniques commonly found in manufacturing, engineering, and research and development endeavors.
Topics covered in the training material include: ODBC, Bar Charts, Histograms, Boxplots, Pareto Charts, Scatterplots, Tables and Chi-Square Analysis, Measures of Location and Variation, t- Tests, Proportion Tests, Tests for Equal Variances, Power and Sample Size, Correlation, Simple Linear and Multiple Regression, ANOVA and GLM
Prerequisite: None. This course is a prerequisite for all other general Minitab courses.
Title
Objectives
Overview of
Understand the Minitab file structure.
MINITAB
Navigate the Minitab environment using the Project Manager
Learn to use Minitab windows, menus, toolbars, and StatGuide
Graphical Analysis
Perform basic graphical and statistical analysis
Display bar chart and Pareto chart.
Update a graph after changing data in the worksheet.
Edit graphs after they have been displayed.
Basic Data
Use histograms and boxplots to analyze data.
Analysis
Calculate descriptive statistics to examine important features of data.
Title
Objectives
Importing &
Enter data into a Minitab worksheet.
Manipulation Data
Import data from other software programs, including Microsoft Excel and Access.
Create and run Exec files to re-create analysis steps
Display Pareto charts, bar charts to represent data.
Use Minitab tools to recode data and create new variables
Restructure data for analysis in Minitab
Statistical
Evaluate the difference between a process (population) mean and a target value
Inference and t-
using a 1-sample t-test and confidence intervals.
Tests
Assess the power of a hypothesis test using power analysis
Test for a difference between two population means using a 2-sample t-test.
Test for a difference between paired observations using a paired t-test.
Proportion Tests
Determine the appropriate sample size for a 1-proportion test.
Determine whether a defect rate is different from the target value using the 1-
proportion test.
Determine whether defect rates are different from one another using the 2-
proportions test.
Analysis of
Assess the power of an analysis of variance using power analysis.
Variance
Compare group variances using a variance test.
Compare means for samples collected at different levels using a general linear
model.
Perform ANOVA with more than one factor.
Interpret interaction plots and multiple comparisons.
Chi-Square
Test the independence between categorical variables.
Analysis
Understand the contribution of each combination to the overall test.
Correlation and
Measure the degree of linear association between two or more variable using
Regression
correlation.
Model the relationship between a continuous response variable and a predictor
variable.
Multiple
Perform regression analysis with more than one predictor.
Regression
Handle multicollinearity in a regression analysis.
Programme scope, delivery arrangements and suitability are confirmed during enquiry.