In this course, you will :
- Able to interpret descriptive statistics, causal analyses and visualizations to draw meaningful insights.
- Introduces a conceptual framework for considering the various purposes of statistical analysis
- How data is used by analysts for descriptive, causal, and predictive inference
- How to design an effective visualisation, compute and interpret descriptive statistics, and create a research study for causal analysis.
- Explore various methods for quantifying these concepts.
- The course starts with an overview of the various levels of measurement and methods for transforming variables.
- Discuss the construction and construction of a measurement model.
- Focuses on how analysts can quantify and describe their confidence in their findings
- How to run a hypothesis test with test statistics and confidence intervals
- Data – What It Is, What We Can Do With It
- Measurement – Turning Concepts into Data
- Quantifying Relationships with Regression Models
- What are the Chances? Probability and Uncertainty in Statistics
- Data Literacy Capstone – Evaluating Research