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Basic Applied Statistics 1000
Solutions to Practice Midterm 1
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- (ii)Crunchy (stemplot is centered around higher values)
- (ii)Crunchy's somewhat more variable (stemplot has more spread)
- (ii) Crunchy (stemplot has longer right tail, whereas Creamy has a
slightly longer left tail, when configured on an axis with lower values
to the left, higher values to the right)
- 1st, 5th, average of 9th and 10th, 14th, 18th: 34,42,51,62,80
- IQR=62-42=20; Q1-1.5(IQR)=42-1.5(20)=12
- yes
- (i) Creamy (min is 22, max is 68, etc.)
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- (ii) histogram (1 quantitative variable)
- (ii) mean and standard deviation, because the distribution should
be fairly normal
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- (iv) scatterplot (2 quantitative variables)
- (iv) report the correlation
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- (iii) side-by-side boxplots (1 quantitative variable plus 1 categorical
variable)
- (iii) Compare Five Number Summaries (there could be right skewness/high
outliers)
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- .9505 (look up proportion LESS than +1.65)
- approximately 1
- .0160 (subtract proportion for -1.4 from proportion for -1.3; proportions
CANNOT be negative, so I took off 3 pts. for an answer of -.016)
- Look up a proportion of .8000 below, and find z=.84
- Look up a proportion of .1000 and find z=-1.28
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- (iii) 3 is a parameter mu because it describes the entire population
- Half are below the mean, 3.0
- Take mean plus or minus 3 standard deviations: between 2.7 and 3.3
- x>3.14 means z>-1.4, look up proportion less than +1.4: .0808
- .09 below has z=-1.34, so x=3-1.34(.1)=2.866
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- number of persons
- (i) increase
- (ii) moderate
- (v) .63 (this could also be found by taking the square root of R-Sq=.396)
- (ii) stay the same; r is independent of units of measurement
- 4.55+0.996(1)=5.546
- 6.83-5.546=1.284
- (ii) Take the number of people and add 4.55
- 2 (Number of persons=2 clearly has the most extreme residual, and it's
even singled out as an outlier in the output at the bottom of the page.
However, I only took off 2 points if you didn't notice the residual for 2,
and thought the one for 6 persons was the most extreme.)
- (ii) 10 people discarding 4 pounds (This is the only one of the three
that is way off the regression line, and the fact that its x-value is far
from the rest could give it a lot of influence.)
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- (ii) (In this design, a treatment---encouraging mothers to
breast-feed---is imposed.)
- (i) 200 is the sample size, the number of individuals actually studied
- (ii) infants not participating are the control
- (ii) income/education is a possible lurking variable, which is tied
in with whether or not a baby is breastfed, and could also impact the
likelihood of infection. (i) is in fact the explanatory variable, (iii) is
the response.
- (ii) random assignment to treatment or control is essential; I
mentioned coinflipping in class as a viable way to make assignements
- (ii) The fact that mothers must know they are being encouraged to
breast-feed rules out the possibility of a double-blind study. It would
certainly be possible to make it blind on the part of doctors: they wouldn't
have to know if a baby has been breast-fed when they are diagnosing for
infection.
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- 4+4(.25)=5
- 4(.05)=.2
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