EViews Mastery: Data Analysis and Econometric Modeling
EViews Mastery: Data Analysis and Econometric Modeling, available at $54.99, has an average rating of 3.5, with 171 lectures, based on 2 reviews, and has 414 subscribers.
You will learn about Mastering the EViews graphical user interface (GUI) for efficient navigation and data handling. Performing descriptive statistical analysis to summarize data distributions and trends. Generating log returns and understanding their implications in financial and economic contexts. Creating and interpreting correlation matrices to explore relationships between variables. Constructing scatter plots to visualize data points and identify patterns or outliers. Applying volatility analysis techniques to assess risk and uncertainty in time series data. Utilizing advanced features for econometric modeling and hypothesis testing. Implementing forecasting models to predict future trends based on historical data. Integrating real-world data sets into EViews for practical application and analysis. Developing analytical skills to make informed decisions and recommendations in economic and financial research. This course is ideal for individuals who are Students and Researchers: Those studying economics, finance, or related fields who need to analyze data using EViews for academic projects or research. or Professionals: Working in finance, economics, or data analysis roles who require skills in econometric modeling and forecasting using EViews. or Analysts and Consultants: Interested in enhancing their data analysis capabilities for economic and financial data using advanced statistical techniques. or Educators: Teaching economics or finance courses who want to incorporate practical data analysis and econometric methods into their curriculum. or Anyone Interested: Individuals keen on learning EViews for personal or professional development in data analysis and econometrics. It is particularly useful for Students and Researchers: Those studying economics, finance, or related fields who need to analyze data using EViews for academic projects or research. or Professionals: Working in finance, economics, or data analysis roles who require skills in econometric modeling and forecasting using EViews. or Analysts and Consultants: Interested in enhancing their data analysis capabilities for economic and financial data using advanced statistical techniques. or Educators: Teaching economics or finance courses who want to incorporate practical data analysis and econometric methods into their curriculum. or Anyone Interested: Individuals keen on learning EViews for personal or professional development in data analysis and econometrics.
Enroll now: EViews Mastery: Data Analysis and Econometric Modeling
Summary
Title: EViews Mastery: Data Analysis and Econometric Modeling
Price: $54.99
Average Rating: 3.5
Number of Lectures: 171
Number of Published Lectures: 171
Number of Curriculum Items: 171
Number of Published Curriculum Objects: 171
Original Price: $99.99
Quality Status: approved
Status: Live
What You Will Learn
- Mastering the EViews graphical user interface (GUI) for efficient navigation and data handling.
- Performing descriptive statistical analysis to summarize data distributions and trends.
- Generating log returns and understanding their implications in financial and economic contexts.
- Creating and interpreting correlation matrices to explore relationships between variables.
- Constructing scatter plots to visualize data points and identify patterns or outliers.
- Applying volatility analysis techniques to assess risk and uncertainty in time series data.
- Utilizing advanced features for econometric modeling and hypothesis testing.
- Implementing forecasting models to predict future trends based on historical data.
- Integrating real-world data sets into EViews for practical application and analysis.
- Developing analytical skills to make informed decisions and recommendations in economic and financial research.
Who Should Attend
- Students and Researchers: Those studying economics, finance, or related fields who need to analyze data using EViews for academic projects or research.
- Professionals: Working in finance, economics, or data analysis roles who require skills in econometric modeling and forecasting using EViews.
- Analysts and Consultants: Interested in enhancing their data analysis capabilities for economic and financial data using advanced statistical techniques.
- Educators: Teaching economics or finance courses who want to incorporate practical data analysis and econometric methods into their curriculum.
- Anyone Interested: Individuals keen on learning EViews for personal or professional development in data analysis and econometrics.
Target Audiences
- Students and Researchers: Those studying economics, finance, or related fields who need to analyze data using EViews for academic projects or research.
- Professionals: Working in finance, economics, or data analysis roles who require skills in econometric modeling and forecasting using EViews.
- Analysts and Consultants: Interested in enhancing their data analysis capabilities for economic and financial data using advanced statistical techniques.
- Educators: Teaching economics or finance courses who want to incorporate practical data analysis and econometric methods into their curriculum.
- Anyone Interested: Individuals keen on learning EViews for personal or professional development in data analysis and econometrics.
Introduction:
Welcome to the “EViews Essentials” course, your gateway to mastering econometric analysis and statistical modeling using EViews. Whether you’re a student, researcher, or professional in finance, economics, or related fields, this course is designed to equip you with practical skills and theoretical knowledge essential for data-driven decision-making.
EViews, renowned for its robust capabilities in time series analysis and econometric modeling, provides a powerful platform to explore, analyze, and forecast data. Throughout this course, you will delve into various modules, each designed to deepen your understanding and proficiency in using EViews for statistical analysis, regression modeling, time series analytics, and more.
From navigating the EViews GUI to advanced topics like VAR modeling, ARCH modeling, and co-integration testing, you will gain hands-on experience through practical examples and projects. By the end of this course, you will not only be proficient in leveraging EViews for data analysis but also capable of applying these skills to real-world scenarios effectively.
Let’s embark on this journey to unlock the full potential of EViews and enhance your analytical toolkit for making informed decisions in complex economic and financial landscapes.
Section 1: EViews GUI Introduction to EViews through its graphical user interface (GUI), focusing on navigation essentials and basic tools. Students learn to efficiently navigate datasets, access statistical tools, and perform basic operations within EViews.
Section 2: Descriptive Statistics in EViews This section dives into descriptive statistics using EViews. Students start by generating log returns, a fundamental metric in financial analysis. They then explore interpreting graphs and analyzing volatility patterns, essential for understanding data distributions and trends.
Section 3: Correlation Techniques in EViews Advanced correlation techniques are covered here. Students learn to generate correlation matrices to identify relationships between variables. Practical skills include creating scatter plots and interpreting correlation data to make informed analytical decisions.
Section 4: Project on EViews – Regression Modeling Regression modeling is a cornerstone of statistical analysis. This section covers basic regression modeling theory and practical application in EViews. Students learn to generate estimation outputs, interpret regression results, and analyze scatter plots for regression diagnostics.
Section 5: Univariate Time Series Analytics & Modeling with EViews Univariate time series analysis focuses on understanding and modeling data that changes over time. Students implement correlograms to analyze data patterns and interpret ARMA (AutoRegressive Moving Average) models for forecasting and decision-making.
Section 6: Project on EViews – Multivariate Modeling Multivariate modeling expands on univariate concepts to analyze relationships between multiple variables simultaneously. Students work with estimation outputs, interpret scatter plots, and apply modeling techniques to complex datasets, such as financial and economic data.
Section 7: Auto-correlation Techniques in EViews Auto-correlation analysis is crucial for understanding relationships within time series data. Students learn to use EViews for Durbin Watson analysis, residual diagnostics, and interpreting Ordinary Least Squares (OLS) equations to detect and address autocorrelation.
Section 8: Project on EViews – VAR Modeling Vector Autoregressive (VAR) modeling is a powerful tool for analyzing the dynamic relationships between multiple time series variables. Students study VAR modeling theory, generate VAR estimates, perform impulse response tests, and interpret variance decompositions to understand the impact of shocks and relationships between variables.
Section 9: Stationarity and Unit Root Testing in EViews Stationarity and unit root testing are essential for time series modeling. Students learn to apply Dickey Fuller tests in EViews to determine the stationarity of data series and interpret unit root tests to understand the long-term behavior and trends in time series data.
Section 10: Co-integration Testing in EViews Co-integration testing assesses the long-term equilibrium relationship between variables. Students implement Johansen integration tests in EViews to analyze co-integration relationships, perform trace tests and eigenvalue tests, and interpret the results to understand the economic relationships between variables.
Section 11: Project on EViews – Volatility and ARCH Modeling Volatility and ARCH (AutoRegressive Conditional Heteroskedasticity) modeling focus on analyzing and forecasting volatility in financial markets. Students explore ARCH modeling theory, estimate GARCH (Generalized Autoregressive Conditional Heteroskedasticity) models, interpret volatility spikes, and analyze the impact of volatility on asset prices and risks.
Each section of this course provides hands-on experience with EViews, equipping students with essential skills in data analysis, statistical modeling, and econometric applications suitable for various industries, including finance, economics, and research.
Conclusion:
Starting with the fundamentals of EViews GUI navigation and descriptive statistics, you progress through advanced topics such as regression modeling, VAR modeling, ARCH modeling, and co-integration testing. Each section equips you with practical skills to analyze data, interpret results, and derive meaningful insights for decision-making in finance, economics, and beyond.
As you move forward, continue to explore and apply your newfound knowledge in real-world scenarios. Whether you’re analyzing economic trends, forecasting financial markets, or conducting research, the skills acquired in this course will serve as a solid foundation.
Remember, EViews is a powerful tool that enables you to uncover hidden patterns, test hypotheses, and make data-driven predictions. Stay curious, keep practicing, and leverage these skills to excel in your academic pursuits or professional career.
Thank you for joining us on this learning journey. We wish you success in all your future endeavors in econometrics and data analysis with EViews.
Course Curriculum
Chapter 1: EViews GUI
Lecture 1: Introduction to Eview Training
Lecture 2: Eviews GUI
Lecture 3: Eviews GUI Continues
Chapter 2: Descriptive Statistics in Eviews
Lecture 1: Generating Log Returns
Lecture 2: Example of Descriptive
Lecture 3: Interpretation and Graphs
Lecture 4: Interpretation and Graphs Continues
Lecture 5: Generating Log Returns and Descriptive
Lecture 6: Generating Log Returns and Descriptive Continue
Lecture 7: Example of Interpretations
Lecture 8: Volatility Graphs
Lecture 9: Generating returns Interpretation and Graphs
Lecture 10: Generating returns Interpretation Continues
Chapter 3: Correlation Techniques in Eviews
Lecture 1: Basic Correlation Theory
Lecture 2: Generating Correlation Matrix in Eviews
Lecture 3: Generating Correlation Matrix in Eviews Continues
Lecture 4: Mutual Funds Correlation Matrix Percentage
Lecture 5: Scatter Plots Using Eviews
Lecture 6: Generating Correlation Matrix
Lecture 7: Scatter Plots and Volatility Graphs
Lecture 8: Generating Correlation Matrix and Interpretations
Lecture 9: Generating Correlation Interpretations
Lecture 10: Generating Correlation Interpretations Continues
Lecture 11: Scatter Plots
Lecture 12: Working on Scatter Plots
Chapter 4: Project on EViews – Regression Modeling
Lecture 1: Basic Regression Modelling Theory
Lecture 2: Generating Returns and Estimation Output
Lecture 3: More on Generating Returns
Lecture 4: Understanding Estimation Output
Lecture 5: Understanding Estimation Output Continues
Lecture 6: Example of Interpretations
Lecture 7: Generating Estimation Output
Lecture 8: Interpretations and Volatility Scatter Plots
Lecture 9: More on Volatility Scatter Plots
Lecture 10: Estimation Output Interpretations and Graphs
Lecture 11: Estimation Output Interpretations and Graphs Continues
Lecture 12: Example 3 – NAV Price Study
Lecture 13: Working on Volatility Graphs
Lecture 14: Correlation Matrix
Lecture 15: Correlation Matrix Continues
Lecture 16: Example 4 – Estimation Output
Lecture 17: Basic Regression Modelling
Lecture 18: Basic Regression Modelling Continues
Lecture 19: Interpretations and Scatterplot Analysis
Lecture 20: More on Scatterplot Analysis
Lecture 21: Equation Estimation
Chapter 5: Univariate Time Series Analytics & Modeling with Eviews
Lecture 1: Univariate Time Series Modelling
Lecture 2: Example of Univariate Time Series Modelling
Lecture 3: Understanding and Implementing Correlogram
Lecture 4: Correlogram Analysis
Lecture 5: Correlogram Analysis Continues
Lecture 6: Estimation Output Analysis and Interpretation
Lecture 7: Interpretation of the ARMA Model
Lecture 8: Interpretation of the ARMA Model Continues
Lecture 9: Correlogram Estimation of Output Model
Lecture 10: Correlogram Estimation of ARMA Model
Lecture 11: More on ARMA Model
Lecture 12: Correlogram and Estimation Output for ARMA Model
Chapter 6: Project on EViews – Multivariate Modeling
Lecture 1: Need of Multivariate Modelling
Lecture 2: Basic Theory Multivariate Modelling
Lecture 3: Generating Estimation Outputs
Lecture 4: Generating Estimation Outputs Continues
Lecture 5: Interpretations of Estimation Output
Lecture 6: Interpretations Cost Of Debt
Lecture 7: Scatter Plots Example
Lecture 8: Indices and Commodities
Lecture 9: Estimations Outputs
Lecture 10: Interpretations and Scatter Plots
Lecture 11: Generating Estimation Outputs Example 3
Lecture 12: More on GE Outputs Example 3
Lecture 13: Interpretations of Example 3
Lecture 14: Interpretations of Example 3 Continues
Chapter 7: Auto-correlation Techniques in Eviews
Lecture 1: Durbin Watson
Lecture 2: Durbin Watson Continues
Lecture 3: Residual Diagnostics
Lecture 4: DW Analysis
Lecture 5: Estimation output and DW interpretations
Lecture 6: OLS Equation and Estimation Output
Lecture 7: OLS Equation and Estimation Output Continue
Lecture 8: Example of Gold and BSE Index
Lecture 9: Example of Gold and BSE Index Continue
Lecture 10: DW Calculated
Lecture 11: Example of Forex and Index
Lecture 12: Example of Forex and Index Continue
Lecture 13: Multi Asset Analysis
Lecture 14: Correlation Matrix
Lecture 15: Estimation Output Interpretation
Lecture 16: Breusch Godfrey Test
Lecture 17: Importing Data
Lecture 18: Steps Of Breusch
Lecture 19: Steps Of Breusch Continue
Lecture 20: Correlogram and LM test
Lecture 21: Correlogram and LM test Continue
Instructors
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