Math 151 , Day 31, Monday, April 19, 2004 hit reload...After class

HW Day31  Sec. 6.1 Read it again.  read ahead, Sec. 6.2 at least to p. 334.  I will ask you Friday to tell me  some new words we'll need to understand.    (I have a MISPRINT p. 329, tan box, first formula::  z = x -BAR minus mu-sub-zero (etc.), not z = x minus mu-sub-zero (etc.) as written.  If your book is newer, this may be fixed.)
Memorize the definition of a C.I. p. 302, esp. the "repeated samples" bit, or definition below,
                and the formula p.306 for a CI for the mean (or below) (including where z* comes from!).
    Closed Book Quiz Wednesday  on the two Confidence Interval things.
Mr. Shilepsky will be teaching Wednesday's class.  I will be out of town, back Friday.
Note on reading:  p. 306, table at top:  "Tail area" is area in One tail, which is what you look up in the Normal table.
Hand in, Sec.6.1 : 
6.5 IQ test scores Read pp. 312-13 before doing this one. (already assigned)
6.3 density of x-bar, and confidence intervals. This problem combines the text Figures 6.2 and 6.4 For part d, to draw the confidence interval:  just choose any point on the horizontal axis of  your graph to be x-bar (Like me at the board, my head being xbar).  Measure off the distance m (half the width of the shaded interval) and extend a bar m wide to the left and the right of your point,below the curve (My arm length was m).  (Like fig. 6.4, the bars with arrows at the ends.  The red dots show what the x-bar is for that confidence interval)  Choose another point, and repeat..  If your first x-bar was in the shaded interval, pick your second outside the shaded interval, and vice versa.  You should note that if x-bar is in the shaded interval, then the confidence interval bar covers mu (280) and if x-bar isn't, then the bar doesn't. 
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A.  Shoeboxes: Separate sheet: You can get a sample of 4 each  outside my door, or in class Wed.  For each sample of size  4 from a shoebox, find the mean, (know which box you got them from: which: white #s, green box, yellow, red top) and tell whether you believe the population mean for that box is 20, or something bigger.  Bring to class Friday to pool.  The shoeboxes are outside my door if you missed doing them in class.
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Cautions; general review and extension 
 p. 314 6.14 internet, response rate
 p.317, 6.19 newts
p. 318, 6.22  men/women CI's
 p.316, 6.18  consumers/pharmacies
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 review 
p. 315, 6.16  enlighten the unstatistical
  6.17hotel mgrs.
= = = = = = = = = = = = = = 
Postpone: Sample size for C.I.
p. 3.11, 6.10, 6.11, 6.12 
Read, 
to discuss
Optional

Forgot to do: New Shoeboxes:  Take 4 from each, write them down (White from green box, yellow from red-top box) For HW, find means (for each box separately.)  Know  which box!  Does that box have pop. mean 20, or some number >20?

Closed book quiz Wednesday:  1)  Give a definition of a level C Confidence Interval for a parameter.
2) a) Write down the formula for a level C confidence interval for the unknown mean of a normal population.
       (Assume the standard deviation of the population is known.)
    b) Tell, or show with a picture,  how "C" connects with your formula.
# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Confidence interval estimate of a(n unknown) population parameter:

Confidence Interval of the form  estimate + margin-of-error  for the mean µ with Confidence level C: (p.306) (Table A, or Table C, t dist. bottom row) The Birkenstock box contains numbers from a normally distributed population, with population standard deviation 2.
You each constructed a 60% confidence interval for the unknown mean:
    n = 4.
    Standard deviation of sample mean = 2/sqrt(4) = 2/2 = 1
    z* for C = 60% is .841 (table C) , so margin of error m is .841 x 1= .841.
How many people captured the true mean?
( previous classes,11/20 = 55% ,  22/29= 76%.   9/18 = 50% , 11/20 = 55%,  15/22= 68%,  16/24 = 67%
Combined, 84/133 = 63.2%   This class?  16/18 = 88%  Combined 100/151 = 66%
Quite variable for small samples, but settling down?)
Homework questions?

Why does the formula work?

Assumptions: pp. 312-13
SRS--other random samples get other formulas.  Nonrandom or biased  samples can't use C.I.
    Sometimes we can plausibly think of data as SRS from large population (rolling dice, repeated weighings on scale)
Xbar is normal!  OK IF 1) population is normal, or 2) n big enough for Central Limit theorem.
    Outliers?  Trouble (xbar is sensitive).   Slight outliers ok (see next)
    Skewness?  n> 15 allows CLTh to overcome all but strong skewness.
Sigma for population is known.  Rarely true in practice.  Large n?  substitute s calculated from sample. Small n--Ch. 7.

Relation of m (margin of error, half width), C (confidence level), and n (sample size), (and sigma)
    C and z* get bigger and smaller together (bigger C means bigger z*, and vice versa) (standard normal sketch)
,    m = z* (sigma)/ sqrt(n)
    Want bigger C?  Must accept bigger m.  Trade off confidence vs. accuracy.
    But bigger n will make smaller m. This makes sense: bigger sample size, more info-->more accurate estimate.
            (square root makes it Expensive: have to quadruple n to make m half as  big)
    So smaller m can be achieved only by
        » accepting lower confidence level (smaller C),
        » or by increasing sample size (bigger n).

Visual example: Author website, whfreeman.com/scc, Applet: Confidence Intervals.
      You can change the C, with the same xbars, see the m change.  (n and sigma are fixed.)
        (50 intervals display. More will overwrite the drawings of old ones.  But they accumulate numerically  in the right panel till you reset.)

    Sigma:  We can't change it, it comes with the population.  But bigger sigma (more population variability) will give bigger m (wider CI), i.e. less accuracy in prediction (for the same C and n).
Science  projects directed by Prof. Wahl:  Experiments on chickens bred to be "identical"--very low variability from one to the other.  Therefore very small samples suffice.

Start here Wednesday??:
Planning ahead:  Choose sample size big enough to satisfy desired: margin of error, confidence level.
Given C and m (and sigma), find n.
   Method:  Use C to find z*.  Plug in to formula for m, and solve for n.  Or memorize formula for n and plug in to it.
,    n = (z* sigma / m)2
     Note:  z* sigma still on top.  m and n change places, and whole thing is squared!
           Round up!  If you get n = 5.06, you need a sample of size 6 to get your margin of error at least as short as you want.
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Sec 6.2: "Significance tests use an elaborate vocabulary, but the basic idea is simple: an outcome that would "rarely" happen if a claim were true--is good evidence that the claim is NOT true." (p.314)


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