Data Analytics (LGVR)
This curricular unit includes Statistics concepts and tools that allow you to analyze data and obtain results in a meaningful and useful way for management and decision-making in Retail problems. The presentation of content is made from an applied perspective and is accompanied by data analysis software, to assist in describing and visualizing data, as well as exploring relationships, comparisons, conduct predictive models and identifying patterns.
Data analysis
Statistical inference
Predictive models
Communication of results
Upon completion of the CU, the student is expected to demonstrate abilities to:
- Apply data visualization and descriptive statistics tools, interpreting in context;
- Identify situations of uncertainty modeled by some of the most important probability distribution laws;
- Determine Confidence intervals and Hypothesis Tests on parameters to support decision;
- Conduct and interpret correlation and regression relationships, such as predictive models (sales, satisfaction, etc.)
- Know and apply some methods of forecasting and data mining.
- Use software, critically evaluate and communicate the results
1. Introduction to data analysis. Tools, data cleansing. Data visualization, relationships, descriptive statistics;
2. Probability, Distribution Laws and Bayes' Formula
3. Estimation and Inference: Sampling, Confidence Intervals and Hypothesis Tests (parametric and non-parametric).
4. Correlation analysis and Regression (predictive models).
5. Additional topics: to be selected between Time Series and forecast. Decision trees, classification
Applications with software (SPSS, or R, Python, others, at no additional cost to the student).
P. Newbold, W. L. Carlson, & B. M. Thorne (2019). Statistics for Business and Economics. 9. ed., Boston: Pearson S.
Christian Albright, Wayne L. Winston. Business Analytics: Data Analysis & Decision Making, 7th edition, CENGAGE, 2019
Text materials and other types to be made available online by the teacher.
E-learning.
Continuous assessment is privileged: 2 digital written documents (e-folios) during the semester (40%) and a final digital test, Global e-folio (e-folio G) at the end of the semester (60%). In due time, students can alternatively choose to perform one final exam (100%).