STAT 101 Lecture Notes - Lecture 3: Scatter Plot, Dependent And Independent Variables
24 May 2017
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Document Summary
Material covered in week 3 - corresponds to ch. Study topic of regression, following logically from material in week 2. Generally speaking, regression - concerns modelling of response variable by 1/more explanatory variables. Although many approaches to regression, this chapter focuses on linear modelling of quantitative response variable in terms of single quantitative explanatory variable. Regression has been active research topic for 100 years. We only touch on some of basics of regression. Begins w/ paired data (x 1 ,y 1 ), ,(x n ,y n ) where y = quantitative response variable. Attempt to determine straight line approximation y = a + bx corresponding to and x = quantitative explanatory variable paired data. A and b = intercept and slope. Although many ways to determine straight line, expressions for a and b given in textbook referred to as least squares estimates. ** know how to calculate least squares estimates a and b & that understand rationale of least squares.
