Data Analysis using EViews course

Course Date Duration Location Registration
29/04/2024 To 10/05/2024 10 Days Nairobi Kenya
27/05/2024 To 07/06/2024 10 Days Nairobi Kenya
24/06/2024 To 05/07/2024 10 Days Nairobi Kenya
22/07/2024 To 02/08/2024 10 Days Nairobi Kenya
19/08/2024 To 30/08/2024 10 Days Nairobi Kenya
16/09/2024 To 27/09/2024 10 Days Nairobi Kenya
14/10/2024 To 25/10/2024 10 Days Nairobi Kenya
11/11/2024 To 22/11/2024 10 Days Nairobi Kenya
02/12/2024 To 13/12/2024 10 Days Nairobi Kenya
16/12/2024 To 27/12/2024 10 Days Mombasa, Kenya

Course Outline

Welcome to the "Data Analysis using EViews" course, where we embark on a journey to master the art of insightful data analysis leveraging the powerful capabilities of EViews. In today's data-driven world, the ability to extract meaningful insights from vast datasets is a valuable skill, and EViews stands as a stalwart companion in this endeavor. This course is designed to cater to individuals across various professional domains, providing a comprehensive understanding of EViews' functionalities and empowering participants to unravel the stories hidden within their data.

As we delve into the intricate world of EViews, participants will gain a solid foundation in fundamental data analysis techniques and progressively advance to sophisticated econometric modeling and time-series analysis. EViews, renowned for its user-friendly interface, is an ideal tool for professionals seeking robust solutions for forecasting, panel data analysis, and more. The course emphasizes hands-on learning, ensuring that participants not only grasp theoretical concepts but also apply them in practical scenarios. By the end of this journey, participants will emerge with the skills necessary to make informed decisions, solve complex problems, and communicate data-driven insights effectively.

Join us on this exciting exploration of data analysis through the lens of EViews, where theory meets practical application, and where participants evolve into adept analysts equipped to navigate the complexities of today's data-rich landscape. Whether you're a seasoned professional or just beginning your journey in data analysis, this course promises a transformative experience, unlocking the potential of EViews as a formidable ally in your pursuit of data mastery.

Course Objectives:

  1. Mastering EViews Fundamentals: Gain proficiency in navigating EViews' interface and understand its core functionalities.
  2. Time-Series Analysis: Develop skills in analyzing time-series data, identifying patterns, and making informed forecasts.
  3. Econometric Modeling: Learn to build and interpret econometric models, exploring relationships within datasets.
  4. Forecasting Techniques: Acquire techniques for accurate and reliable data forecasting using EViews.
  5. Panel Data Analysis: Understand and apply panel data analysis methods to uncover trends and patterns.
  6. Advanced Visualization: Explore advanced data visualization tools within EViews for clear and impactful presentation of results.
  7. Hypothesis Testing: Learn statistical methods to test hypotheses and make data-driven decisions.
  8. Model Validation: Understand techniques for validating models and ensuring their reliability.
  9. Automation and Efficiency: Discover ways to automate repetitive tasks, increasing efficiency in data analysis.
  10. Real-world Applications: Apply EViews skills to real-world scenarios, enhancing practical problem-solving abilities.

Organizational Benefits:

  1. Enhanced Decision-Making: Equip your team with advanced data analysis skills to make informed decisions.
  2. Improved Forecast Accuracy: Increase the accuracy of business forecasts through sophisticated modeling techniques.
  3. Efficient Resource Allocation: Optimize resource allocation by understanding and analyzing patterns in historical data.
  4. Strategic Planning: Develop strategic plans based on robust econometric modeling and data-driven insights.
  5. Risk Mitigation: Identify and mitigate risks through comprehensive data analysis and scenario planning.
  6. Increased Productivity: Streamline workflows and enhance productivity by automating data analysis processes.
  7. Competitive Advantage: Gain a competitive edge by making strategic decisions supported by thorough data analysis.
  8. Cost Savings: Identify cost-saving opportunities through efficient resource allocation and process optimization.
  9. Better Communication: Improve communication of complex data insights within the organization.
  10. Skill Development: Foster a culture of continuous learning and skill development among your team.

Target Participants:

This course is designed for professionals and analysts across various industries who want to enhance their data analysis skills using EViews. It is suitable for economists, finance professionals, researchers, business analysts, and anyone involved in decision-making processes that rely on data.

Course Outline

Module 1: Introduction to EViews

  1. Overview of EViews interface and features.
  2. Importing and organizing data in EViews.
  3. Understanding different data types and formats.
  4. Basic operations and data manipulation techniques.
  5. Introduction to EViews scripting for automation.
  6. Case studies: Hands-on practice with basic data analysis.

Module 2: Exploratory Data Analysis (EDA) in EViews

  1. Descriptive statistics and data summarization.
  2. Visualizing data distributions using graphs and charts.
  3. Handling missing data and outliers in EViews.
  4. Correlation and covariance analysis.
  5. Time-series exploration for trend and seasonality.
  6. Case studies: Applying EDA techniques to real datasets.

Module 3: Time-Series Analysis in EViews

  1. Time-series data concepts and structures.
  2. EViews tools for time-series decomposition.
  3. Seasonal adjustment techniques.
  4. AutoRegressive Integrated Moving Average (ARIMA) models.
  5. Forecasting methods and accuracy evaluation.
  6. Case studies: Forecasting future trends using EViews.

Module 4: Econometric Modeling with EViews

  1. Basics of econometric modeling.
  2. Model specification and hypothesis testing.
  3. Estimation methods in EViews.
  4. Interpreting regression output.
  5. Diagnostic testing and model validation.
  6. Case studies: Building and analyzing econometric models.

Module 5: Panel Data Analysis in EViews

  1. Introduction to panel data and its advantages.
  2. Fixed and random effects models.
  3. Testing for panel data assumptions.
  4. Dynamic panel data models.
  5. EViews tools for panel data visualization.
  6. Case studies: Analyzing longitudinal data in EViews.

Module 6: Advanced Visualization in EViews

  1. Customizing graphs and charts in EViews.
  2. Geographic data visualization using maps.
  3. Interactive dashboards and report generation.
  4. Exporting and sharing visualizations.
  5. Visualizing regression diagnostics.
  6. Case studies: Communicating insights through compelling visuals.

Module 7: Hypothesis Testing and Statistical Inference

  1. Overview of hypothesis testing in EViews.
  2. One-sample and two-sample hypothesis tests.
  3. Chi-square tests and analysis of variance (ANOVA).
  4. Non-parametric tests in EViews.
  5. Power analysis and effect size.
  6. Case studies: Applying statistical tests to real-world scenarios.

Module 8: Model Validation and Robustness

  1. Validation techniques for econometric models.
  2. Sensitivity analysis and robustness testing.
  3. Overfitting and regularization methods.
  4. Out-of-sample testing and cross-validation.
  5. Addressing multicollinearity issues in EViews.
  6. Case studies: Ensuring reliability and accuracy in models.

Module 9: Forecasting Methods and Applications

  1. Advanced time-series forecasting techniques.
  2. Evaluating forecast accuracy metrics.
  3. Seasonal adjustment and trend forecasting.
  4. Volatility modeling and forecasting.
  5. Long-term forecasting using EViews.
  6. Case studies: Implementing advanced forecasting models.

Module 10: Automation and Efficiency in EViews

  1. Scripting basics and automation workflows.
  2. Batch processing and repetitive task automation.
  3. Creating custom procedures and functions.
  4. Integration with external data sources.
  5. Efficiency tips and best practices.
  6. Case studies: Streamlining analysis workflows in EViews.

Module 11: Real-world Applications of EViews

  1. Industry-specific data analysis applications.
  2. Case studies from finance, economics, and business.
  3. Addressing challenges in real-world datasets.
  4. Ethical considerations in data analysis.
  5. Reporting and communicating results effectively.
  6. Group projects: Applying EViews to real-world scenarios.

Module 12: Advanced Time-Series Analysis

  1. Advanced concepts in time-series modeling.
  2. Seasonal adjustment and decomposition methods.
  3. ARIMA modeling with exogenous variables.
  4. Unit root tests and stationarity.
  5. Time-varying parameter models.
  6. Case studies: Analyzing complex time-series data.

Module 13: Dynamic Panel Data Models

  1. Dynamic panel data concepts.
  2. GMM estimation methods.
  3. Testing for endogeneity and instrument selection.
  4. Time-varying effects in panel data.
  5. EViews tools for dynamic panel visualization.
  6. Case studies: Implementing dynamic panel models.

Module 14: Multivariate Analysis in EViews

  1. Multivariate regression analysis.
  2. Principal Component Analysis (PCA).
  3. Factor analysis in EViews.
  4. Canonical correlation analysis.
  5. Multivariate time-series modeling.
  6. Case studies: Analyzing relationships among multiple variables.

Module 15: Cointegration and Error Correction Models

  1. Understanding cointegration and its implications.
  2. Engle-Granger and Johansen cointegration tests.
  3. Implementing error correction models in EViews.
  4. Testing for long-run relationships.
  5. Time-series integration and stationarity.
  6. Case studies: Applying cointegration in economic modeling.

Module 16: Machine Learning Integration with EViews

  1. Introduction to machine learning in EViews.
  2. Supervised and unsupervised learning techniques.
  3. Regression and classification models.
  4. Model evaluation and validation in EViews.
  5. Feature selection and model interpretability.
  6. Case studies: Integrating machine learning in EViews analysis.

Module 17: Spatial Data Analysis with EViews

  1. Introduction to spatial data analysis.
  2. Spatial autocorrelation and clustering.
  3. Geostatistical modeling in EViews.
  4. Mapping and visualization of spatial data.
  5. EViews tools for spatial econometrics.
  6. Case studies: Analyzing spatial patterns and relationships.

Module 18: Event Study Analysis in EViews

  1. Understanding event study methodologies.
  2. Designing event study frameworks in EViews.
  3. Estimating abnormal returns and event windows.
  4. Statistical testing in event studies.
  5. Visualization and interpretation of event study results.
  6. Case studies: Conducting event studies in EViews.

Module 19: EViews Add-ins and Extensions

  1. Overview of EViews add-ins and extensions.
  2. Installing and managing add-ins.
  3. Exploring popular EViews extensions.
  4. Customizing EViews with third-party tools.
  5. Creating and sharing custom add-ins.
  6. Case studies: Enhancing EViews functionality with add-ins.

Module 20: Capstone Project

  1. Integrating skills from previous modules.
  2. Choosing and analyzing a real-world dataset.
  3. Developing and presenting a comprehensive analysis.
  4. Peer review and feedback session.
  5. Enhancing project documentation and reporting.
  6. Graduation and certification ceremony.

General Information

  1. Customized Training: All our courses can be tailored to meet the specific needs of participants.
  2. Language Proficiency: Participants should have a good command of the English language.
  3. Comprehensive Learning: Our training includes well-structured presentations, practical exercises, web-based tutorials, and collaborative group work. Our facilitators are seasoned experts with over a decade of experience.
  4. Certification: Upon successful completion of training, participants will receive a certificate from Foscore Development Center (FDC-K).
  5. Training Locations: Training sessions are conducted at Foscore Development Center (FDC-K) centers. We also offer options for in-house and online training, customized to the client's schedule.
  6. Flexible Duration: Course durations are adaptable, and content can be adjusted to fit the required number of days.
  7. Onsite Training Inclusions: The course fee for onsite training covers facilitation, training materials, two coffee breaks, a buffet lunch, and a Certificate of Successful Completion. Participants are responsible for their travel expenses, airport transfers, visa applications, dinners, health/accident insurance, and personal expenses.
  8. Additional Services: Accommodation, pickup services, freight booking, and visa processing arrangements are available upon request at discounted rates.
  9. Equipment: Tablets and laptops can be provided to participants at an additional cost.
  10. Post-Training Support: We offer one year of free consultation and coaching after the course.
  11. Group Discounts: Register as a group of more than two and enjoy a discount ranging from 10% to 50%.
  12. Payment Terms: Payment should be made before the commencement of the training or as mutually agreed upon, to the Foscore Development Center account. This ensures better preparation for your training.
  13. Contact Us: For any inquiries, please reach out to us at training@fdc-k.org or call us at +254712260031.
  14. Website: Visit our website at www.fdc-k.org for more information.

 

 

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