QMS 102 Lecture Notes - Lecture 2: Missing Data, Cluster Sampling, Sampling Frame

• School: Ryerson University
• Department: Quantitative Methods
• Course: QMS 102
• Professor: Fu

Document Summary

Categorical (qualitative) variables take categories as their values such as yes , no , or blue , Numerical (quantitative) variables have values that represent a counted or measured quantity. Need to avoid data flawed by biases, ambiguities, or other types of errors. Results from flawed data will be suspect or in error. Even the most sophisticated statistical methods are not very useful when the data is flawed. The data collector is the one using the data for analysis. The person performing data analysis is not the data collector. Examining data from print journals or data published on the internet. Examples of data distributed by organizations or individuals: Financial data on a company provided by investment services. Industry or market data from market research firms and trade associations. Stock prices, weather conditions, and sports statistics in daily newspapers. A survey asking people which laundry detergent has the best stain-removing abilities. Political polls of registered voters during political campaigns.