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Lecture 12

STAT 2230 Lecture 12: Day 12: Analysis [Feb 03]
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2 Pages
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Department
Statistics
Course Code
STAT 2230
Professor
Andrew Mc Adam

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Description
Day 12: Analysis [Feb 03] - ///// late - picked up on page 29 - how do we use this to make a statistical hypothesis test? - either: - the two population mean score is 14 and I just obtained a particularly under-performing sample, OR - I should not have been assuming that μ = 14 in the first place - more negative T-scale - small p-value - p = 0.0034 for this problem - which means there is very strong evidence against the null hypothesis - very strong evidence against the claim that students are performing at the correct level - example: chocolate chips - in 1998, Nabisco ran an advertising campaign in which they claimed that each 18-ounce bag of Chips Ahoy cookies would contain at least 1000 chocolate chips - test this claim - population: all bags of cookies - mean # of chips = μ - standard deviation = sigma - null hypothesis: H​ : 0​= 1000 - alternate hypothesis: H​ : μ > 1000 A​ - a group of consumers purchased a sample of bags of cookies and counted the number of chocolate chips in each bag - what sort of evidence would convince you that Nabisco were telling the truth? - I would be convinced by large sample means - T = (​ȳ - ​μ)​ / (​s​/sqrt(n)) - large positive T → small p - in reality, the sample had n = 50 observations with a sample mean of ȳ = 1175 number of chocolate chips per bag, with a standard deviation of s = 292 - T = (​ȳ - ​μ)​ / (​s​/sqrt(n)) → assume that the H​ 0​ true, and u
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