Description
Advanced Data Visualization with Stata
Duration:
10 Days
Course Level:
Advanced
Target Audience
- Data Analysts
- Statisticians
- Researchers who need to learn Advanced Data Visualization with Stata
- Financial Analysts
- Epidemiologists and Biostatisticians
- Business Analysts
- Consultants who need to learn Advanced Data Visualization with Stata
Course Objectives
- Understand both descriptive and inferential statistics
- Master various data collection techniques and data processing methods
- Use mobile phones for data collection (Open Data Kit)
- Navigate basic functions and features within Stata
- Create and manipulate graphs and figures using Stata
- Annotate data, set out command functions, and create/execute Do files
- Utilize Stata effectively for data manipulation and analysis
- Maintain organized records of your work and create reproducible analyses
- Export results and generate reports from your analyses
Module 1: Introduction to Advanced Graphics in STATA
- Overview of graphical capabilities in STATA
- Customizing graph types and features
- Exporting and saving graphs
- Advanced graph options and settings
- Case Study: Comparing sales trends across different regions using line and bar graphs
Module 2: Data Visualization Techniques
- Creating scatterplots and adding regression lines
- Histograms and density plots
- Boxplots and violin plots for distributions
- Multi-panel graphs for comparative analysis
- Case Study: Visualizing customer satisfaction scores by demographic factors
Module 3: Complex Tabulations and Summaries
- Generating frequency tables
- Cross-tabulations and chi-square tests
- Summary statistics with multiple group comparisons
- Using table and tabstat commands
- Case Study: Analyzing survey responses to identify patterns and correlations. All these in Advanced Data Visualization with Stata
Module 4: Handling Missing Data in Graphics
- Identifying missing data patterns
- Visualizing missing data with graphs
- Strategies for dealing with missing data in analyses
- Implementing imputation methods
- Case Study: Assessing the impact of missing data on survey results
Module 5: Advanced Regression Analysis
- Multiple regression modeling
- Interaction effects and moderating variables
- Diagnostics and model validation
- Visualizing regression results with graphs
- Case Study: Evaluating the effect of marketing strategies on sales performance
Module 6: Time Series Analysis and Visualization
- Plotting time series data
- Decomposition and trend analysis
- Seasonal effects and forecasting
- Time series regression and autocorrelation
- Case Study: Analyzing monthly stock prices for trend and seasonality
Module 7: Panel Data Analysis
- Creating and managing panel datasets
- Fixed effects vs. random effects models
- Visualizing panel data results
- Interpreting coefficients and model fit
- Case Study: Examining economic growth indicators across countries over time
Module 8: Advanced Statistical Tests and Procedures
- ANOVA and MANOVA techniques
- Non-parametric tests and their applications
- Post-hoc analysis and comparisons
- Visualizing results from statistical tests
- Case Study: Comparing treatment effects across different patient groups
Module 9: Multivariate Analysis and Visualization
- Principal Component Analysis (PCA)
- Factor Analysis and dimensionality reduction
- Cluster analysis and visualization
- Interpreting multivariate results with graphs
- Case Study: Segmenting customer data for targeted marketing strategies
Module 10: Customizing and Automating Graphics
- Writing custom graph scripts
- Automating repetitive graph tasks
- Creating graph templates and styles
- Sharing and integrating custom graphics with reports
- Case Study: Developing a customized reporting dashboard for financial analysis
