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L17-ss

# L17-ss - The UNIVERSITY of NORTH CAROLINA at CHAPEL HILL...

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6/3/11 Lecture 17 1 STOR 155 Introductory Statistics Lecture 17: Hypothesis Testing Section 6.2 The UNIVERSITY of NORTH CAROLINA at CHAPEL HILL

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6/3/11 Lecture 17 2 Point estimation – to estimate a parameter (quick and easy) Confidence interval – to estimate a parameter with measures for reliability and accuracy attached Hypothesis testing – hypothesis: a statement about the parameters – to assess whether the data provide enough evidence for some claim about the population Procedures for statistical inference
6/3/11 Lecture 17 3 Confidence Interval • Point estimate with margin of error • Confidence interval for a population mean – Assumption: the population variance is known – Confidence level C determines z * n z x n z x * * ,

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6/3/11 Lecture 17 4 Hypothesis Testing • Sometimes you may not be interested in estimating the parameter value • Rather, you have some claim ( belief ) about the parameter and you want to see whether the data support the claim or not, i.e. to choose between two decisions: `` support ’’ versus `` contradict ’’
6/3/11 Lecture 17 5 “Biased” one-Euro Coin? • A group of statistics students spun the Belgian one-Euro coin 250 times, and heads came up 140 times. p = P (H) in each spin • Claim : the coin is biased (more specifically, p is greater than 0.5)

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6/3/11 Lecture 17 6 • Two hypotheses H 0 : the null hypothesis • the statement of “no effect” or “no difference” • the statement we try to find evidence against H a : the alternative hypothesis • the statement we hope or suspect to be true • Usually H a is based on a ``hint’’ from samples Concepts of Hypothesis Testing
Lecture 17 7 “Biased” one-Euro Coin? (continued) • Sample: 140 heads among 250 spins of a Belgian one-Euro coin (a hint ) p = P (H) in each spin H 0 : p = 0.5 vs H a : p > 0.5. – one-sided

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L17-ss - The UNIVERSITY of NORTH CAROLINA at CHAPEL HILL...

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