STAT 1000Q Lecture Notes - Lecture 1: Exploratory Data Analysis, Reliability Engineering, Statistical Hypothesis Testing
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Stat 1000 lecture 1 - introduction & overview. A standard approach to statistical analysis primarily for students of. Data business and economics; elementary probability, sampling distributions, normal theory estimation and hypothesis testing, regression and correlation, exploratory data analysis. Learning to do statistical analysis on a personal computer is an integral part of the course. Where can statistics be applied: numeric summary. De nition and properties of probability, sample spaces, events, algebraic combination of events, conditional probability and independence, the. Law of large numbers: continuous distributions; uniform and normal distributions, sampling distributions. Economics: estimation; forecasts of macroeconomic data. This is important, especially in elds such as aerospace. Agriculture: new fertilizers/pesticides versus old/existing ones, new crop strains versus old/existing ones. Politics: surveys based on opinion, how does one select a scienti c sample, how does one determine the margin of error in survey. Testing of certain chemicals in the environment: effect on cancer and disease rates.
