Statistics in a Modern World 800
Solutions to Practice Final Exam
- (c) observational study
-
- source: American Journal of Clinical Nutrition (study done by FDA)
- researchers:? (doctors presumably assessed whether or not women had the
genetic abnormality; perhaps other doctors assessed Down syndrome)
- individuals: mothers
- measurements: presence or absence
of genetic abnormality, Down syndrome or not
- setting:? (hospital and/or doctor's office?)
- compare women with the genetic abnormality to women without
- those with abnormality are 2.6 times likelier to have Down syndrome child
- (c) more than 1000 (otherwise we wouldn't have enough cases of Down
syndrome, which occurs in 1 out of 600)
- (b) possible interacting variables ("something else has to help trigger
the devastating condition")
- (a) explanatory variable
- (b) bargraph
-
- (i) invalid (not measuring what they're supposed to)
- (ii) unreliable (measurements not consistent)
-
- median is between 15th and 16th values, or 116.5
- (ii) fairly symmetric
- (ii) mean about equal to median
- 8th value, or 106
-
- z=(110-100)/8=1.25; proportion with z above +1.25 = proportion with
z below -1.25 = .11
- shortest 5% have z=-1.64, so observed value = 100-1.64(8) = 86.88
-
- 3.6 + .97(55) = 56.95
- (ii) older, because the slope +.97 is positive
-
- 2
- 4
- 1
- 5
- 3
-
- null hypothesis: no relationship between drinking and smoking; alternative
hypothesis: there IS a relationship
- expected counts are 162, 108, 198, 132
- compared counts are 2, 3, 1.6, 2.5
- chi-squared statistic = 2+3+1.6+2.5 = 9.1
- p-value less than .05, since chi-squared is greater than 3.84
- yes, because we reject the null hypothesis with a small p-value
- (calculations are in terms of thousands of miles)
- null hypothesis: mean duration = 22; alternative hypothesis: mean
duration less than 22
- z= (21.8-22)/(1.2/10) = -1.67
- p-value = probability of z below -1.67 = .05
- (iii) results are borderline
-
- .33 + .20 = .53
- 1 - .53 = .47
-
- no: .34(.05) is not equal to .03
- .34 + .05 - .03 = .36
-
- 1/2 * 1/2 * 1/2 * 1/2 = 1/16
- (iii) a total of 2 boys and 2 girls can happen in several ways:
BBGG or BGBG or BGGB or GBGB or GBBG or BBGG
- 500(.9) - 1500(.1) = 300
- (b) getting a queen (most general)
- (g) conservatism
- (a) anchoring
- (e) optimism
- (b) availability
-
- .01(.8) = .008
- .99(.1) = .099
- .008 + .099 = .107
-
-
- .5
- square root of .5(1-.5)/81 = .056
- approximately normal
- .444 and .556
- .388 and .612
- .332 and .668
-
- 52/81 = .64
- SE = square root of .64(1-.64)/81 = .053; interval is .64 plus or minus
2(.053) = (.53, .75)
-
- null hypothesis: proportion of women = .5; alternative hypothesis:
proportion of women > .5
- SE = square root of .5(1-.5)/81 = .056, so z= (.64-.5)/.056 = 2.5
- p-value = probability of z above 2.5 = probability of z below -2.5
= .005
- (ii) small p-value means reject the null and conclude the alternative
is true
-
- 68.2 plus or minus 2(2.7/square root of 200) = (67.8, 68.6)
- 95% of the time, an interval constructed by this method will in fact
contain the unknown population mean. Alternatively, I am 95% confident that
mean height of all men is between 67.8 and 68.6.
- (a) combine results if studies have quite similar conditions
- (b) keep results separate if studies have quite different conditions
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