BUSS1020 Lecture Notes - Lecture 1: Categorical Variable, Nominal Level

• School: University of Sydney
• Department: Business Studies
• Course: BUSS1020
• Professor: Erick Li

Document Summary

Define the problem, objective and data required (design) Organize the data clean it, prepare for analysis, tabulate, and summarize. Methods that collect, describe and transform data into insight for decision makers: Predicitve (using a model to make forecasts) Inferential (drawing conclusions on large samples from small data sets) Summarize business data (to visualize and summarize) Variable: charactersitcs of an item or individual (often called attributes). Data: are the observed outcomes of one or more variables. Population: consists of all the items of individuals which a conclusion is being drawn on (the large group) Sample: a smaller protion of a popularion selected for analaysis. Parameter: numerical measure that describes a relevant characteristics of a population. Statistic: numerical measure that describes the character of a sample. Categorical (qualitative): variables have values that can be placed into catergories. Numerical (quantitative) variables have results that represent actual number quantities: discrete from a counting process, continuous from a measuring process.