Topics covered

1. Introduction to Data Analytics and today’s world
2. Descriptive Statistics (Qualitative and Quantitative)
3. Measures of Variability
4. Basic Theory of Probability 
5. Probability distributions 
6. Practice with z-tables
7. Goodness of fit and Independence tests (chi-square)
8. Confidence Intervals
9. Hypothesis Testing 
10. Introduction to Regression Analysis
11. Statistics software – Excel 
12. Data Visualization software – Google Analytics, Tableau, Heat Maps and more

*Extended subjects such as multiple regressions, cluster analysis, two way anova, forecasting, experimental design are available for enriched courses. 

Learning Objectives

1. • Analyze the process of data collection and identify different types of measurements
   • Describe and discuss collected data using various graphical, tabular and numerical summary methods
   • Engage with the notion of probability and sampling through the role of making decisions in a similation project
   • Express in report format storytelling to various audiences
   • Engage in feedback loops and adapt to improvements
   • Conduct their own research project and create their experimental designs
   • Use statistical softwares relevant to the workplace such as Excel, Pivot tables
   • Experiment with data visualization softwares available in the market (Tableau, heatmaps, google analytics) 

Topics covered

1. Interacting Positively with Others
2. Getting what you want
3. Presenting yourself in writing 
4. Interview Process
5. Handling Career Challenges
6. Building Relationships at Work
7. Developing your career

Learning Outcomes

1. State short and long-term career plans
2. Identify one’s transferable skills
3. Seek and compile a list of employment opportunities, and identify general trends emerging in the business work environment
4. Develop a list of contacts through various networking techniques
5. Prepare, modify, and update a résumé
6. Formulate appropriate business letters