Predictive Modeling| Statistical Analysis: Minitab and Excel

Leverage Minitab and Excel to master predictive modeling, statistical analysis, and data-driven insights.

What you'll learn
Fundamentals of predictive modeling and statistical analysis.
How to navigate and use Minitab for data analysis.
Descriptive statistics, hypothesis testing, and regression modeling.
Correlation analysis and its applications.
Using Excel's Analysis ToolPak for regression and other statistical techniques.

Requirements
Basic understanding of statistics and data analysis concepts. Access to Minitab software and MS Excel. Familiarity with data manipulation and basic computations.

Description
Course IntroductionPredictive modeling and statistical analysis are essential for informed decision-making across industries. This course empowers you to apply Minitab and Excel to analyze data, uncover trends, and create robust models. Covering everything from descriptive statistics to regression modeling, this course provides practical examples with datasets from real companies like Infosys, Reliance, and Colgate Palmolive.Section-wise WriteupSection 1: IntroductionThe course begins with an introduction to predictive modeling using Minitab. Students will learn the software's capabilities and gain a foundational understanding of its interface and purpose in statistical analysis.Section 2: Getting StartedThis section explores Minitab's basic features. You'll learn to compute column statistics, navigate the software's windows, and use the Help and Assistant features effectively for guided analysis.Section 3: Descriptive StatisticsDive into descriptive statistics with case studies from Reliance and Infosys. This section teaches how to summarize data, calculate central tendencies, and draw insights. You'll practice hands-on examples, progressing from simple statistics to hypothesis testing with t-tests for comparative analysis.Section 4: Chi-Square and ANOVA TestingIn this section, you’ll explore Chi-square tests and Analysis of Variance (ANOVA) for assessing statistical independence and comparing group means. Examples from real-world scenarios solidify your understanding, ensuring you can apply these techniques confidently.Section 5: CorrelationsCorrelations are key to understanding relationships between variables. This section covers correlation analysis in depth, breaking it down into three parts for clarity. You'll learn to quantify and interpret associations between datasets effectively.Section 6: Linear Regression ModelingLearn to build and interpret linear regression models with examples from companies like Tech Mahindra, Colgate Palmolive, and BSE. This section delves into the theoretical foundation of regression and applies it to real-world data, ensuring you gain both conceptual and practical expertise.Section 7: MS Excel for Statistical AnalysisThe course concludes with an introduction to using MS Excel for regression analysis. You’ll install and use the Analysis ToolPak add-in to perform statistical computations, providing an accessible alternative for analysis.ConclusionThis course equips you with the tools and techniques to perform predictive modeling and statistical analysis using Minitab and Excel. By combining theoretical concepts with practical applications, you'll be prepared to tackle real-world data challenges.

Who this course is for
Students and professionals seeking hands-on statistical analysis experience.
Analysts and researchers looking to enhance their skills with Minitab and Excel.
Business and data science enthusiasts interested in predictive modeling.