Predictive Modeling and Data Analysis with Minitab and Excel

Predictive Modeling & Data Analysis with Minitab & Excel

This comprehensive course equips you with the skills to leverage statistical techniques for predictive modeling and in-depth data analysis. Whether you're a beginner or an experienced data analyst, gain valuable insights and practical experience applying predictive modeling methods to real-world datasets. Learn to analyze data, build predictive models, and make informed decisions.

Throughout this course, you'll master Minitab, a powerful statistical software, and Microsoft Excel, a widely-used tool, to perform various data analysis and predictive modeling tasks. We provide a step-by-step guide to mastering key techniques.

By the end, you'll have the confidence to:

• Analyze data effectively.
• Build predictive models for informed decision-making.
• Gain a competitive edge in data analysis.

Course Sections:

Section 1: Introduction to Predictive Modeling

Understand the fundamentals of predictive modeling and its applications across industries. Explore non-linear regression for modeling complex data relationships. Learn about ANOVA (Analysis of Variance) and control charts for variance analysis and quality control. Practical demonstrations using Minitab will guide you through model interpretation and implementation.

Section 2: ANOVA with Minitab

Dive deeper into ANOVA techniques using Minitab. Master pairwise comparisons and chi-square tests to analyze differences between multiple groups. Apply ANOVA to real-world scenarios, including analyzing preference and pulse rate data, and comparing financial plans in mutual funds. Learn to analyze NAV and repurchase prices for financial insights.

Section 3: Correlation Techniques

Explore correlation techniques to understand relationships between variables. Learn basic and advanced correlation methods using Minitab. Interpret correlation results for diverse datasets like return rates and heart rate data. Analyze demographics and living standards to identify socio-economic correlations. Visualize relationships with graphical implementations of correlation.

Section 4: Regression Modeling

Master regression modeling, a powerful technique for analyzing relationships and making predictions. Learn to identify independent and dependent variables. Develop and interpret regression equations for datasets like energy consumption and stock prices. Cover multiple regression analysis (addressing multicollinearity) and logistic regression for predictive analysis of categorical outcomes.

Section 5: Predictive Modeling in Excel

Utilize Microsoft Excel for predictive modeling. Learn to leverage Excel's Data Analysis Toolpak to perform descriptive statistics, ANOVA, t-tests, correlation, and regression analysis. Gain proficiency in applying predictive modeling techniques using Excel's intuitive interface. Ideal for professionals who prefer Excel for data analysis.