Description:
This course will provide an introduction to statistical analysis and data modeling. We will learn the fundamentals of descriptive and inferential statistics and their application. We will also explore the analysis of time series data and modeling business problems. Further, the application of statistical learning models, such as linear and logistic regression, will be examined. Learners will be introduced to the R programming language and will perform data exploration, analysis, modeling and visualization using RStudio.
Course Code/Duration:
BDT154 / 2 Full Days Or 4 Half Days
Learning Objectives:
After this course, you will be able to:
- Install R and RStudio on a personal computer.
- Understand the basics of Descriptive and Inferential Statistics
- Perform exploratory data analysis.
- Use R for data visualization.
- Effectively clean and prepare data for analysis.
- Perform hypothesis testing.
- Utilize Linear Regression for prediction.
- Utilize Logistic Regression for classification.
- Evaluate models and choose the most effective one.
- Understand how to interpret a Confusion Matrix.
- Use R for statistical analysis.
- Perform trend analysis.
- Use time series data for forecasting.
- Understand project workflow for model building.
- Solidify your understanding of statistical analysis and model building by completing hands-on exercises and milestones.
- Understand the importance of statistical analysis and forecasting in business.
- This course is for learners who would like to become familiar with Jupyter Notebook and to max-imize its use for data analysis and for project organization and collaboration.
Training material provided: Yes (Digital format)
