Example Report for Lab 1

Example Assignment: Lab 1, problems 1 and 4

1. Use the sum and sqrt functions to find the mean and
standard deviation of the climate$rain data set:

> climate$rain->z
> sum(z)/50->meanrain
> meanrain
[1] 31.597

> sum((z-meanrain)**2)->temp
> sqrt(temp/49)->sdrain
> sdrain
[1] 13.65638

> stats(z)->check

> check
                   [,1]
             N 50.00000
          mean 31.59700
      Std.Dev. 13.65638
           min  7.11000
            Q1 20.65000
        median 32.55500
            Q3 39.85500
           max 59.74000
missing values  0.00000

4. Plot January versus July temperatures, comment on any
relationships, and identify unusual points:

> climate->z
> view(z,3)
47  remaining rows have not been listed
        lat  jan  rain        city  jul elev        lon
 1 35.08333 22.3  8.12 albuquerque 92.8 5300 -106.65000
 2 33.75000 32.6 48.61 atlanta     87.9 1034  -84.38333
 3 30.28333 38.8 31.50 austin      95.4  570  -97.75000

> set.panel(2,1)
plot window will lay out plots in a 2 by 1 matrix

> plot(z$jan,z$jul)
> title("July Temp. (y) vs. January Temp. (x)")

> plot(z$jan,z$jul)
> text(z$jan,z$jul,z$city)
> title("July Temp. vs. Jan. Temp. with Labels")

Phoenix, Miami, Honolulu, and the West Coast cities (Portland,
San Jose, etc.) are unusual compared to the others.  All except
Phoenix can be explained by proximity to oceans.  Phoenix gets
very hot in the summer but also pretty cool in the winter.
For the other cities it appears that there is a positive
linear relationship between July and January temperatures. That
is, if the January temperature is relatively high for a city,
then the July temperature will tend to be relatively high as well.