Data Analysis for Business Decisions: Case Studies in Excel, R, and ChatGPT 3rd Edition By Andres Fortino
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- 441
- File size
- 23.85 MB
- Format
- Digital PDF
- Course
- Business
- Category
- eBook[PDF]
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About this ebook
The 3rd edition of "Data Analysis for Business Decisions: Case Studies in Excel, R, and ChatGPT" by Andres Fortino is a hands-on guide that teaches business analysts how to frame analytical questions, apply statistical methods, and utilize modern tools to make data-backed business decisions. [1, 2, 3, 4]
The book covers the following key topics and core themes, organized through practical, real-world case studies: [1, 2]
1. Foundations of Business Analytics
- Framing Analytical Questions: Parsing and translating complex business information needs into structured, computable questions.
- Data Preparation: Strategies for data cleaning, gathering, and shaping data sets to make them ready for analysis. [1, 2, 3, 4]
2. Descriptive & Inferential Statistics
- Basic Descriptive Statistics: Core techniques including data summarization, tabulation, and understanding data distributions.
- Inferential Statistics: Hypothesis testing for continuous variables (such as t-Tests) and categorical variables (such as Chi-Square analysis). [1, 2, 3]
3. Advanced Predictive Techniques & Modeling
- Linear & Multivariate Regression: Building predictive models to understand relationships between business variables.
- Time Series Forecasting: Projecting future business trends, sales, and metrics using historical data patterns.
- Contingency Analysis: Exploring relationships between categorical variables to support operational choices. [1, 2, 3]
4. Modern Business Experiments & Text Mining
- A/B Testing: Designing and evaluating randomized experiments to optimize digital marketing strategies or product features.
- Text Analytics: Processing and analyzing qualitative, unstructured text data to extract sentiment and thematic insights. [1, 2, 3]
5. Big Data & Data Visualization
- Big Data Management: Scaling analytics workflows to effectively handle, manipulate, and explore massive datasets.
- Data Visualization: Transforming raw analytics data into impactful, executive-ready charts and visual stories. [1, 2, 3, 4, 5]
6. Multi-Tool Application (Excel, R, Python, and ChatGPT)
- Excel Frameworks: Mastering foundational and advanced spreadsheet operations for everyday business problems. [1, 2, 3, 4]
- R & Python Programming: Leveraging code-based environments for data manipulation, deeper statistical modeling, and handling larger datasets. [1, 2]
- Generative AI Integration: Incorporating platforms like ChatGPT to clean data, interpret charts, generate code snippets, and accelerate the business analysis workflow. [1, 2]
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