ATHK1001 Lecture Notes - Lecture 7: Quartile, Central Tendency, Descriptive Statistics

• School: University of Sydney
• Department: Analytical Thinking
• Course: ATHK1001
• Professor: bruce burns

Document Summary

Quantitative data: steps to take to insure trustworthy data, thorough literature review, identify and minimise bias and systematic error, replication result that cannot be replicated may indicate a (cid:498)fluke(cid:499) Possible use of meta-analysis - methods focused on contrasting and combining results from different studies, in the hope of identifying patterns among study results, sources of disagreement among those results: types of data. Almost anything can be measured, whether directly observable or not. Two types of data: quantitative data an amount or quantity, length, qualitative a quality or category (nominal), voting, nationality, ranks etc. Measurement is the ratio of a continuous quantity and a unit of magnitude. E. g. weight, age, expenditure: interval scale, summarising data. Measures degree of difference, but not ratio. Temperature in c or f, date etc. Also known as descriptive statistics summarises the data and organizes it in a way that is easily accessible. Most common to summarize two aspects of numerical data.