This introductory lecture covers the fundamentals of data analytics and business analytics. It introduces the types of data, including qualitative and quantitative, and categorizes analytical methods into descriptive, predictive, and prescriptive approaches. The session also addresses key legal and ethical considerations related to data analytics.

In this lecture, we introduce data wrangling, which is the process of cleaning, transforming, and managing raw data so it is more reliable and can be more easily accessed and used for the analysis. We then proceed to a detailed discussion of the six steps in data wrangling, beginning with the discovery step to the publishing step. 

In this lecture, we provide an introduction to descriptive statistics that can be used to summarize data. We began by explaining the difference between descriptive and inferential statistics. We then introduce measures of location as well as measures of variability. Lastly, we provide measures of shape and measures of association between two variables.