PDB_Stat_100_Lecture_20_Printable

# PDB_Stat_100_Lecture_20_Printable - STA 100 Lecture 20 Paul...

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STA 100 Lecture 20 Paul Baines Department of Statistics University of California, Davis February 23rd, 2011

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Admin for the Day I Homework 5 due today at 5pm! I For Q2, please test at level α = 0 . 05 I Midterms are ready for pickup. . . I Midterm solutions are posted I Project groups assigned I Project Proposals due Friday! I Possible project datasets will be posted shortly References for Today: Rosner, Ch 7.1-7.7, 8 (7th Ed.) References for Friday: Rosner, Ch 8 (7th Ed.)
Midterm Feedback People generally did well on the midterm (better than midterm I), but there was fairly high variance. . . I Mean: 69 I Median: 72 I SD: 14.8 Histogram. . .

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60 80 100 0 10 20 30 40 50 Histogram of Midterm II Scores Score Frequency
Grade Interpretation You can think of your midterm II scores as being curved, below is a general guideline for how well you did. . . General guidelines for interpreting your score: I 80-100: Excellent I 60-80: Good I 45-60: Fair I 30-45: Poor

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Exam Feedback I Make sure you know how to use a calculator! I Don’t write too much – many answers were unnecessarily long. . . I Please read the solutions – the ﬁnal is cumulative!
Midterm Question 1 Sloths. . . I Estimates and CI – Excellent (except calculations) I Was it trustworthy? Check n ˆ p and n (1 - ˆ p ) conditions! I Hypothesis test – Mixed bag. . . 1. Hypotheses are about parameters not estimates! There are never any ‘hats’ in the hypotheses! 2. Don’t recompute your CI! The CI gives you plausible values – you just use those to check your hypothesis.

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Midterm Question 2 Malaria. . . I Estimates and CI – Excellent (except calculations) I For 2c – data is still Poisson, not normal! Use Poisson formulae. I For 2d – part (c) computed this for one week. You had 52 weeks of data, so remember to multiply by 52. I For 2e: 1. Assumptions are: (i) Independence across weeks, (ii) Each week has same mean, λ , and, (iii) Each week has a Poisson distribution. 2. Your estimate is not an assumption!!! 3. Your estimates would change, but this doesn’t directly address the question. . .
Midterm Question 3 Wine-making. . . I Excellent – parts (a), (b), (c) very similar to homework and practice midterm I Good – (d), (e), (f) recognize this is a linear combination I For part 3(f), this was a very tricky question. . . , 1. You might think that the probability of a blended wine being dull has to be between the two component wines – but. . . 2. The mean acidity level has to be inbetween the two means 3. The SD has to be inbetween the two SDs – but it’s nonlinear. . . 4. With proportion c of Chardonnay, the SD is p c 2 × 0 . 12 2 + (1 - c ) 2 × 0 . 04 2 . 5. If we choose c = 0 . 2 we can do better!

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Hypothesis Testing We have covered the basic methodology of hypothesis testing I Formulate a real-world hypothesis as a concrete statistical assumption (e.g., μ = μ 0 ) I Decide what alternative hypothesis we wish to consider (e.g., μ < μ 0 , μ > μ 0 or μ 6 = μ 0 ) I Go collect some data I Work out how likely it is that you would have got the answer you did, or even more convincing evidence against H 0 , if the null hypothesis were true (the p - value) I Compare that probability to how often you are willing to be wrong (is the p -
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PDB_Stat_100_Lecture_20_Printable - STA 100 Lecture 20 Paul...

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