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Using STATA: 1.The data file water.dta were collected in an investigation of environmental causes of disease. They show the annual mortality per 100,000 for males,

Using STATA:

1.The data file water.dta were collected in an investigation of environmental causes of disease. They show the annual mortality per 100,000 for males, averaged over the years 1958-1964, and the calcium concentration (in parts per million) in the drinking water for 61 large towns in England and Wales. The higher the calcium concentration, the harder the water.

The four variables are:

location: a factor with levels North and South indicating whether

the town is as north as Derby.

town: the name of the town.

mortality: averaged annual mortality per 100,000 male inhabitants.

hardness: calcium concentration (in parts per million).

With these data

1)Construct a scatterplot for the calcium concentration (in parts per million) versus averaged annual mortality per 100,000 male inhabitants. (10 points)

2)Construct a side-by-side histograms of mortality between north and south. (10 points)

Do the histogram plots of mortality look like the normal distribution? (5 points)

3)Construct a side-by-side histograms of hardness between north and south. (10 points)

Do the distribution plots of hardness look like the normal distribution? (5 points)

4)Construct a side-by-side box plot for the mortality between north and south (location). (10 points)

Comment on the difference in mortality between north and south. (5 points)

5)Construct a side-by-side box plot for the hardness between north and south (location). (10 points)

Comment on the difference in hardness between north and south. (5 points)

6)Summarize the mortality using mean and standard deviation between north and south. (10 points)

7)Summarize the hardness using mean and standard deviation between north and south. (10 points)

8)Generate a new variable, loghardness, by taking (natural) logarithm of hardness. Construct a side-by-side histogram of hardness between north and south. Comment if the distributions look closer to the normal distribution than the original scale. (10 points)

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