Master Data Analysis and Visualization: Skills for Insights
School
California State University, Northridge**We aren't endorsed by this school
Course
BUS LAW 308
Subject
Information Systems
Date
Dec 12, 2024
Pages
5
Uploaded by PresidentMagpie4684
Course Title: Data Analysis and VisualizationCourse Description: This course covers the fundamentals of data analysis and visualization, including data cleaning, statistical analysis, and data visualization techniques. Students will learn how to work withdatasets, create visualizations, and communicate insights effectively.Course Objectives:1. Understand the principles of data analysis and visualization.2. Learn how to clean, manipulate, and analyze datasets.3. Develop skills in creating effective data visualizations.4. Understand how to communicate insights and findings effectively.Course Outline:Week 1: Introduction to Data Analysis and Visualization- Overview of data analysis and visualization
- Importance of data-driven decision making- Key concepts and terminologyWeek 2: Data Cleaning and Manipulation- Introduction to data cleaning and manipulation- Handling missing data and outliers- Data transformation and normalizationWeek 3: Statistical Analysis- Introduction to statistical analysis- Descriptive statistics and data visualization- Inferential statistics and hypothesis testingWeek 4: Data Visualization- Introduction to data visualization
- Principles of effective data visualization- Creating visualizations with popular tools (e.g. Tableau, Power BI)Week 5: Communicating Insights and Findings- Introduction to communicating insights and findings- Effective communication strategies- Creating reports and presentationsProject:For this project, students will work in teams to analyze and visualize a dataset of their choice. The project should include the following components:1. A written report outlining the data analysis and visualization process2. A presentation summarizing the findings and insights3. A visualization dashboard created with a popular tool (e.g. Tableau, Power BI)
The project should demonstrate the following skills:1. Data cleaning and manipulation2. Statistical analysis and data visualization3. Effective communication of insights and findingsGrading:The project will be graded on the following criteria:1. Quality of the data analysis and visualization process (30%)2. Effectiveness of the visualization dashboard (30%)3. Quality of the written report and presentation (20%)4. Timeliness and professionalism of the project submission (20%)Resources:- Dataset of choice (e.g. Kaggle, UCI Machine Learning Repository)
- Data analysis and visualization tools (e.g. Tableau, Power BI, R, Python)- Statistical analysis software (e.g. R, Python, SPSS)