1 ## load the data frame normtemp, which is contained in the UsingR package;
   2 ## it contains the body temperature of several individuals,
   3 ## the gender and the heart rate
   4 require(UsingR)
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   7 ## test if the temperature is different in male (coded as 1)
   8 ## and female (coded as 2), use the appropriate test.
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  16 ## shapiro.test (i do not recommend tests)
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  22 ## test again, compare the results of the t test and the wilcoxon.
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  25 ## plot the respective boxplots!
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  30 ## The data set slc contains data on red blood cell sodium-lithium
  31 ## countertransport activity for 190 individuals. Describe the shape
  32 ## of the distribution, estimate the center, state what is an
  33 ## appropriate measure of center for this data.
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  40 ## Load the data set vacation This gives the number of paid holidays
  41 ## and vacation taken by workers in the textile industry.
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  47 ## t test: if appropriate, test the null hypothesis that $\mu = 24$. 
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  50 ## Repeat the above for the Simple data set smokyph. This data set
  51 ## measures pH levels for water samples in the Great Smoky Mountains.
  52 ## Use the waterph column smokyph[[’waterph’]] to
  53 ## test the null hypothesis that mu = 7.
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  63 ## In the babies (UsingR) data set, the variable dht contains the
  64 ## father’s height. Do a significance test of the null hypothesis that
  65 ## the mean height is 68 inches against an alternative that it is taller.
  66 ## Remove the values of 99 from the data, as these indicate missing data.
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  72 ## Suppose a cell-phone bill contains this data for the number
  73 ## of minutes per call:
  74 
  75 call.min <- c(2,1,3,3,3,3,1,3,16,2,2,12,20,31)
  76 
  77 ## Is this consistent with an assumption that the median call
  78 ## length is 5 minutes, or does it indicate that the median length
  79 ## is less than 5?
  80 
  81 require(PASWR)
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  85 ## the babies (UsingR) data set contains data covering many births.
  86 ## Information included is the gestation period, and a factor
  87 ## indicating whether the mother was a smoker. Extracting the rows
  88 ## for mothers who smoked during pregnancy can be done with these commands:
  89 
  90 require(dplyr)
  91 babies <- filter(babies, smoke == 1 & gestation != 999)
  92