Business Statistics and Data Analysis
Statistical and Analytical Courses
This course is for all Marketing, Sales, HR, Business Analysts and Managers who routinely analyze data for business application. Areas of focus are foundation statistics, distribution analysis, capability assessment, graphing, comparison tests and sample size selection. This course is designed for 16 hours of presentation.

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Download the full curriculum for Statistical and Analytical courses in PDF format.

Biotech, Pharmaceutical & Medical Device Courses

Systematic product development, Quality by Design courses, consulting services and analytical training for biotechnology, pharmaceutical and medical device industries. QbD provides guidance to facilitate design of products and processes that maximize the product’s efficacy and safety profile while enhancing product manufacturability and control.

Lean Six Sigma

Complete curriculum for new product development, manufacturing and business process performance optimization.

Tools & Templates

Development tools and templates created by Thomas A. Little Consulting have been used by numerous companies to aid and support various aspects of product development, problem solving, data analysis and risk assessment.

This course is required for all Marketing, Sales, HR, Business Analysts and Managers who routinely analyze data for business application.
There are no prerequisites for this course.
Course Objectives
  1. Understand the ideas associated with sampling and data collection.
  2. Demonstrate the ability to evaluate distributions.
  3. Select appropriate sample sizes for performance evaluation.
  4. Conduct comparative tests using data.
  5. Use regression techniques in order to analyze the results and make performance improvements.
  6. Select an appropriate analysis technique based on the type of data.
Detailed Course Outline
Section I: Introduction to JMP
Table commands
Column commands
Row commands
Subset, Stack and Join commands
Saving data and graphs
Section II: Statistics Foundations & Distribution Analysis
Measures of center and spread
Standard error and central limit theorem
Normal distribution, t distribution and confidence intervals
Test for normality
Process capability normal and non-normal distribution fitting
Trend Analysis
Section III: Nominal X, Continuous Y
Sample size for the mean
t test – one sample, two sample and paired
Test for differences in variances
One-way ANOVA
Customer Satisfaction and Nonparametric data analysis
Section IV: Continuous X, Continuous Y
Simple linear regression, correlation
Section V: Nominal X, Nominal Y
Test for proportion data
Chi-square test for defects and proportion defective
Pareto graphs and analysis
Section VI: Continuous X, Nominal Y
Logistic regression