Sampling Distributions for Sample Slopes (College Board AP® Statistics)

Study Guide

Mark Curtis

Written by: Mark Curtis

Reviewed by: Dan Finlay

Sampling distributions for sample slopes

What is the population least-squares regression line?

  • If a response variable, y, has a linear relationship with an explanatory variable, x, then there is a population least-squares regression line

    • This has the equation y with hat on top equals alpha plus beta x

      • where y with hat on top is the predicted response

      • alpha is the population y with hat on top-intercept and beta is the population slope

What is the sample least-squares regression line?

  • A random sample of n observations from the population, open parentheses x subscript i comma space y subscript i close parentheses, has sample least-squares regression line

    • This has the equation y with hat on top equals a plus b x

      • where y with hat on top is the predicted response

      • a is the sample y with hat on top-intercept and b is the sample slope

  • Different samples produce different sample least-square regression lines

    • These all have different sample slopes, b

      • This means sample slopes have a sampling distribution

What is the mean and standard deviation of the sampling distribution for sample slopes?

  • The sampling distribution for sample slopes, b, has

    • a mean of beta

      • this is the population slope

    • and a standard deviation of fraction numerator sigma over denominator sigma subscript x square root of n end fraction

      • where n is the sample size

      • and where sigma is the standard deviation of all population residuals

      • and sigma subscript x equals square root of fraction numerator sum from blank to blank of open parentheses x subscript i minus x with bar on top close parentheses squared over denominator n end fraction end root is the standard deviation of the x-values only

  • In practice, fraction numerator sigma over denominator sigma subscript x square root of n end fraction is not known, so must be estimated from the sample (this estimate is called the standard error)

    • The standard error for sample slopes, s subscript b, is given by the formula s subscript b equals fraction numerator s over denominator s subscript x square root of n minus 1 end root end fraction

      • where n is the sample size

      • and where s equals square root of fraction numerator sum from blank to blank of open parentheses y subscript i minus y with hat on top subscript i close parentheses squared over denominator n minus 2 end fraction end root

      • and s subscript x equals square root of fraction numerator sum from blank to blank of open parentheses x subscript i minus x with bar on top close parentheses squared over denominator n minus 1 end fraction end root

    • Note that s is an estimate for the standard deviation of all population residuals (the standard error of the residuals) and its formula:

      • is based on the residuals, y subscript i minus y with hat on top subscript i, from the sample

      • divides by n minus 2 as two parameters, alpha and beta, need to be estimated

Examiner Tips and Tricks

All the formulas required for the sampling distributions of sample slopes are given in the exam.

What is the sampling distribution for standardized sample slopes?

  • The standardized sample slope is fraction numerator b minus beta over denominator s subscript b end fraction

    • The sampling distribution for standardized sample slopes is a t-distribution with n minus 2 degrees of freedom

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Mark Curtis

Author: Mark Curtis

Expertise: Maths

Mark graduated twice from the University of Oxford: once in 2009 with a First in Mathematics, then again in 2013 with a PhD (DPhil) in Mathematics. He has had nine successful years as a secondary school teacher, specialising in A-Level Further Maths and running extension classes for Oxbridge Maths applicants. Alongside his teaching, he has written five internal textbooks, introduced new spiralling school curriculums and trained other Maths teachers through outreach programmes.

Dan Finlay

Author: Dan Finlay

Expertise: Maths Lead

Dan graduated from the University of Oxford with a First class degree in mathematics. As well as teaching maths for over 8 years, Dan has marked a range of exams for Edexcel, tutored students and taught A Level Accounting. Dan has a keen interest in statistics and probability and their real-life applications.