Problem Set # 3

Regina Mendicino

date()
## [1] "Tue Oct 04 23:57:53 2016"

Due Date: October 4, 2016

Total Points: 32

1 Consider the SSN.txt file from http://myweb.fsu.edu/jelsner/temp/data/SSN.txt. The file contains monthly sunspot numbers since 1851.

  1. Read the data into R. (4) load(SSN.txt)
SSN = read.table("SSN.txt", header = TRUE)
SSN
##     Year   Jan   Feb   Mar   Apr   May   Jun   Jul   Aug   Sep   Oct   Nov
## 1   1851  75.5 105.4  64.6  56.5  62.6  63.2  36.1  57.4  67.9  62.5  51.0
## 2   1852  68.4  66.4  61.2  65.4  54.9  46.9  42.1  39.7  37.5  67.3  54.3
## 3   1853  41.1  42.9  37.7  47.6  34.7  40.0  45.9  50.4  33.5  42.3  28.8
## 4   1854  15.4  20.0  20.7  26.5  24.0  21.1  18.7  15.8  22.4  12.6  28.2
## 5   1855  12.3  11.4  17.4   4.4   9.1   5.3   0.4   3.1   0.0   9.6   4.2
## 6   1856   0.5   4.9   0.4   6.5   0.0   5.2   4.6   5.9   4.4   4.5   7.7
## 7   1857  13.7   7.4   5.2  11.1  28.6  16.0  22.2  16.9  42.4  40.6  31.4
## 8   1858  39.0  34.9  57.5  38.3  41.4  44.5  56.7  55.3  80.1  91.2  51.9
## 9   1859  83.7  87.6  90.3  85.7  91.0  87.1  95.2 106.8 105.8 114.6  97.2
## 10  1860  82.4  88.3  98.9  71.4 107.1 108.6 116.7 100.3  92.2  90.1  97.9
## 11  1861  62.3  77.7 101.0  98.5  56.8  88.1  78.0  82.5  79.9  67.2  53.7
## 12  1862  63.1  64.5  43.6  53.7  64.4  84.0  73.4  62.5  66.6  41.9  50.6
## 13  1863  48.3  56.7  66.4  40.6  53.8  40.8  32.7  48.1  22.0  39.9  37.7
## 14  1864  57.7  47.1  66.3  35.8  40.6  57.8  54.7  54.8  28.5  33.9  57.6
## 15  1865  48.7  39.3  39.5  29.4  34.5  33.6  26.8  37.8  21.6  17.1  24.6
## 16  1866  31.6  38.4  24.6  17.6  12.9  16.5   9.3  12.7   7.3  14.1   9.0
## 17  1867   0.0   0.7   9.2   5.1   2.9   1.5   5.0   4.8   9.8  13.5   9.6
## 18  1868  15.6  15.7  26.5  36.6  26.7  31.1  29.0  34.4  47.2  61.6  59.1
## 19  1869  60.9  59.9  52.7  41.0 103.9 108.4  59.2  79.6  80.6  59.3  78.1
## 20  1870  77.3 114.9 157.6 160.0 176.0 135.6 132.4 153.8 136.0 146.4 147.5
## 21  1871  88.3 125.3 143.2 162.4 145.5  91.7 103.0 110.1  80.3  89.0 105.4
## 22  1872  79.5 120.1  88.4 102.1 107.6 109.9 105.5  92.9 114.6 102.6 112.0
## 23  1873  86.7 107.0  98.3  76.2  47.9  44.8  66.9  68.2  47.1  47.1  55.4
## 24  1874  60.8  64.2  46.4  32.0  44.6  38.2  67.8  61.3  28.0  34.3  28.9
## 25  1875  14.6  21.5  33.8  29.1  11.5  23.9  12.5  14.6   2.4  12.7  17.7
## 26  1876  14.3  15.0  30.6   2.3   5.1   1.6  15.2   8.8   9.9  14.3   9.9
## 27  1877  24.4   8.7  11.9  15.8  21.6  14.2   6.0   6.3  16.9   6.7  14.2
## 28  1878   3.3   6.6   7.8   0.1   5.9   6.4   0.1   0.0   5.3   1.1   4.1
## 29  1879   1.0   0.6   0.0   6.2   2.4   4.8   7.5  10.7   6.1  12.3  13.1
## 30  1880  24.0  27.2  19.3  19.5  23.5  34.1  21.9  48.1  66.0  43.0  30.7
## 31  1881  36.4  53.2  51.5  51.6  43.5  60.5  76.9  58.4  53.2  64.4  54.8
## 32  1882  45.0  69.5  66.8  95.8  64.1  45.2  45.4  40.4  57.7  59.2  84.4
## 33  1883  60.6  46.9  42.8  82.1  31.5  76.3  80.6  46.0  52.6  83.8  84.5
## 34  1884  91.5  86.9  87.5  76.1  66.5  51.2  53.1  55.8  61.9  47.8  36.6
## 35  1885  42.8  71.8  49.8  55.0  73.0  83.7  66.5  50.0  39.6  38.7  30.9
## 36  1886  29.9  25.9  57.3  43.7  30.7  27.1  30.3  16.9  21.4   8.6   0.3
## 37  1887  10.3  13.2   4.2   6.9  20.0  15.7  23.3  21.4   7.4   6.6   6.9
## 38  1888  12.7   7.1   7.8   5.1   7.0   7.1   3.1   2.8   8.8   2.1  10.7
## 39  1889   0.8   8.5   6.7   4.3   2.4   6.4   9.4  20.6   6.5   2.1   0.2
## 40  1890   5.3   0.6   5.1   1.6   4.8   1.3  11.6   8.5  17.2  11.2   9.6
## 41  1891  13.5  22.2  10.4  20.5  41.1  48.3  58.8  33.0  53.8  51.5  41.9
## 42  1892  69.1  75.6  49.9  69.6  79.6  76.3  76.5 101.4  62.8  70.5  65.4
## 43  1893  75.0  73.0  65.7  88.1  84.7  89.9  88.6 129.2  77.9  80.0  75.1
## 44  1894  83.2  84.6  52.3  81.6 101.2  98.9 106.0  70.3  65.9  75.5  56.6
## 45  1895  63.3  67.2  61.0  76.9  67.5  71.5  47.8  68.9  57.7  67.9  47.2
## 46  1896  29.0  57.4  52.0  43.8  27.7  49.0  45.0  27.2  61.3  28.7  38.0
## 47  1897  40.6  29.4  29.1  31.0  20.0  11.3  27.6  21.8  48.1  14.3   8.4
## 48  1898  30.2  36.4  38.3  14.5  25.8  22.3   9.0  31.4  34.8  34.4  30.9
## 49  1899  19.5   9.2  18.1  14.2   7.7  20.5  13.5   2.9   8.4  13.0   7.8
## 50  1900   9.4  13.6   8.6  16.0  15.2  12.1   8.3   4.3   8.3  12.9   4.5
## 51  1901   0.2   2.4   4.5   0.0  10.2   5.8   0.7   1.0   0.6   3.7   3.8
## 52  1902   5.5   0.0  12.4   0.0   2.8   1.4   0.9   2.3   7.6  16.3  10.3
## 53  1903   8.3  17.0  13.5  26.1  14.6  16.3  27.9  28.8  11.1  38.9  44.5
## 54  1904  31.6  24.5  37.2  43.0  39.5  41.9  50.6  58.2  30.1  54.2  38.0
## 55  1905  54.8  85.8  56.5  39.3  48.0  49.0  73.0  58.8  55.0  78.7 107.2
## 56  1906  45.5  31.3  64.5  55.3  57.7  63.2 103.6  47.7  56.1  17.8  38.9
## 57  1907  76.4 108.2  60.7  52.6  42.9  40.4  49.7  54.3  85.0  65.4  61.5
## 58  1908  39.2  33.9  28.7  57.6  40.8  48.1  39.5  90.5  86.9  32.3  45.5
## 59  1909  56.7  46.6  66.3  32.3  36.0  22.6  35.8  23.1  38.8  58.4  55.8
## 60  1910  26.4  31.5  21.4   8.4  22.2  12.3  14.1  11.5  26.2  38.3   4.9
## 61  1911   3.4   9.0   7.8  16.5   9.0   2.2   3.5   4.0   4.0   2.6   4.2
## 62  1912   0.3   0.0   4.9   4.5   4.4   4.1   3.0   0.3   9.5   4.6   1.1
## 63  1913   2.3   2.9   0.5   0.9   0.0   0.0   1.7   0.2   1.2   3.1   0.7
## 64  1914   2.8   2.6   3.1  17.3   5.2  11.4   5.4   7.7  12.7   8.2  16.4
## 65  1915  23.0  42.3  38.8  41.3  33.0  68.8  71.6  69.6  49.5  53.5  42.5
## 66  1916  45.3  55.4  67.0  71.8  74.5  67.7  53.5  35.2  45.1  50.7  65.6
## 67  1917  74.7  71.9  94.8  74.7 114.1 114.9 119.8 154.5 129.4  72.2  96.4
## 68  1918  96.0  65.3  72.2  80.5  76.7  59.4 107.6 101.7  79.9  85.0  83.4
## 69  1919  48.1  79.5  66.5  51.8  88.1 111.2  64.7  69.0  54.7  52.8  42.0
## 70  1920  51.1  53.9  70.2  14.8  33.3  38.7  27.5  19.2  36.3  49.6  27.2
## 71  1921  31.5  28.3  26.7  32.4  22.2  33.7  41.9  22.8  17.8  18.2  17.8
## 72  1922  11.8  26.4  54.7  11.0   8.0   5.8  10.9   6.5   4.7   6.2   7.4
## 73  1923   4.5   1.5   3.3   6.1   3.2   9.1   3.5   0.5  13.2  11.6  10.0
## 74  1924   0.5   5.1   1.8  11.3  20.8  24.0  28.1  19.3  25.1  25.6  22.5
## 75  1925   5.5  23.2  18.0  31.7  42.8  47.5  38.5  37.9  60.2  69.2  58.6
## 76  1926  71.8  69.9  62.5  38.5  64.3  73.5  52.3  61.6  60.8  71.5  60.5
## 77  1927  81.6  93.0  69.6  93.5  79.1  59.1  54.9  53.8  68.4  63.1  67.2
## 78  1928  83.5  73.5  85.4  80.6  77.0  91.4  98.0  83.8  89.7  61.4  50.3
## 79  1929  68.9  62.8  50.2  52.8  58.2  71.9  70.2  65.8  34.4  54.0  81.1
## 80  1930  65.3  49.9  35.0  38.2  36.8  28.8  21.9  24.9  32.1  34.4  35.6
## 81  1931  14.6  43.1  30.0  31.2  24.6  15.3  17.4  13.0  19.0  10.0  18.7
## 82  1932  12.1  10.6  11.2  11.2  17.9  22.2   9.6   6.8   4.0   8.9   8.2
## 83  1933  12.3  22.2  10.1   2.9   3.2   5.2   2.8   0.2   5.1   3.0   0.6
## 84  1934   3.4   7.8   4.3  11.3  19.7   6.7   9.3   8.3   4.0   5.7   8.7
## 85  1935  18.6  20.5  23.1  12.2  27.3  45.7  33.9  30.1  42.1  53.2  64.2
## 86  1936  62.8  74.3  77.1  74.9  54.6  70.0  52.3  87.0  76.0  89.0 115.4
## 87  1937 132.5 128.5  83.9 109.3 116.7 130.3 145.1 137.7 100.7 124.9  74.4
## 88  1938  98.4 119.2  86.5 101.0 127.4  97.5 165.3 115.7  89.6  99.1 122.2
## 89  1939  80.3  77.4  64.6 109.1 118.3 101.0  97.6 105.8 112.6  88.1  68.1
## 90  1940  50.5  59.4  83.3  60.7  54.4  83.9  67.5 105.5  66.5  55.0  58.4
## 91  1941  45.6  44.5  46.4  32.8  29.5  59.8  66.9  60.0  65.9  46.3  38.4
## 92  1942  35.6  52.8  54.2  60.7  25.0  11.4  17.7  20.2  17.2  19.2  30.7
## 93  1943  12.4  28.9  27.4  26.1  14.1   7.6  13.2  19.4  10.0   7.8  10.2
## 94  1944   3.7   0.5  11.0   0.3   2.5   5.0   5.0  16.7  14.3  16.9  10.8
## 95  1945  18.5  12.7  21.5  32.0  30.6  36.2  42.6  25.9  34.9  68.8  46.0
## 96  1946  47.6  86.2  76.6  75.7  84.9  73.5 116.2 107.2  94.4 102.3 123.8
## 97  1947 115.7 133.4 129.8 149.8 201.3 163.9 157.9 188.8 169.4 163.6 128.0
## 98  1948 108.5  86.1  94.8 189.7 174.0 167.8 142.2 157.9 143.3 136.3  95.8
## 99  1949 119.1 182.3 157.5 147.0 106.2 121.7 125.8 123.8 145.3 131.6 143.5
## 100 1950 101.6  94.8 109.7 113.4 106.2  83.6  91.0  85.2  51.3  61.4  54.8
## 101 1951  59.9  59.9  55.9  92.9 108.5 100.6  61.5  61.0  83.1  51.6  52.4
## 102 1952  40.7  22.7  22.0  29.1  23.4  36.4  39.3  54.9  28.2  23.8  22.1
## 103 1953  26.5   3.9  10.0  27.8  12.5  21.8   8.6  23.5  19.3   8.2   1.6
## 104 1954   0.2   0.5  10.9   1.8   0.8   0.2   4.8   8.4   1.5   7.0   9.2
## 105 1955  23.1  20.8   4.9  11.3  28.9  31.7  26.7  40.7  42.7  58.5  89.2
## 106 1956  73.6 124.0 118.4 110.7 136.6 116.6 129.1 169.6 173.2 155.3 201.3
## 107 1957 165.0 130.2 157.4 175.2 164.6 200.7 187.2 158.0 235.8 253.8 210.9
## 108 1958 202.5 164.9 190.7 196.0 175.3 171.5 191.4 200.2 201.2 181.5 152.3
## 109 1959 217.4 143.1 185.7 163.3 172.0 168.7 149.6 199.6 145.2 111.4 124.0
## 110 1960 146.3 106.0 102.2 122.0 119.6 110.2 121.7 134.1 127.2  82.8  89.6
## 111 1961  57.9  46.1  53.0  61.4  51.0  77.4  70.2  55.8  63.6  37.7  32.6
## 112 1962  38.7  50.3  45.6  46.4  43.7  42.0  21.8  21.8  51.3  39.5  26.9
## 113 1963  19.8  24.4  17.1  29.3  43.0  35.9  19.6  33.2  38.8  35.3  23.4
## 114 1964  15.3  17.7  16.5   8.6   9.5   9.1   3.1   9.3   4.7   6.1   7.4
## 115 1965  17.5  14.2  11.7   6.8  24.1  15.9  11.9   8.9  16.8  20.1  15.8
## 116 1966  28.2  24.4  25.3  48.7  45.3  47.7  56.7  51.2  50.2  57.2  57.2
## 117 1967 110.9  93.6 111.8  69.5  86.5  67.3  91.5 107.2  76.8  88.2  94.3
## 118 1968 121.8 111.9  92.2  81.2 127.2 110.3  96.1 109.3 117.2 107.7  86.0
## 119 1969 104.4 120.5 135.8 106.8 120.0 106.0  96.8  98.0  91.3  95.7  93.5
## 120 1970 111.5 127.8 102.9 109.5 127.5 106.8 112.5  93.0  99.5  86.6  95.2
## 121 1971  91.3  79.0  60.7  71.8  57.5  49.8  81.0  61.4  50.2  51.7  63.2
## 122 1972  61.5  88.4  80.1  63.2  80.5  88.0  76.5  76.8  64.0  61.3  41.6
## 123 1973  43.4  42.9  46.0  57.7  42.4  39.5  23.1  25.6  59.3  30.7  23.9
## 124 1974  27.6  26.0  21.3  40.3  39.5  36.0  55.8  33.6  40.2  47.1  25.0
## 125 1975  18.9  11.5  11.5   5.1   9.0  11.4  28.2  39.7  13.9   9.1  19.4
## 126 1976   8.1   4.3  21.9  18.8  12.4  12.2   1.9  16.4  13.5  20.6   5.2
## 127 1977  16.4  23.1   8.7  12.9  18.6  38.5  21.4  30.1  44.0  43.8  29.1
## 128 1978  51.9  93.6  76.5  99.7  82.7  95.1  70.4  58.1 138.2 125.1  97.9
## 129 1979 166.6 137.5 138.0 101.5 134.4 149.5 159.4 142.2 188.4 186.2 183.3
## 130 1980 159.6 155.0 126.2 164.1 179.9 157.3 136.3 135.4 155.0 164.7 147.9
## 131 1981 114.0 141.3 135.5 156.4 127.5  90.9 143.8 158.7 167.3 162.4 137.5
## 132 1982 111.2 163.6 153.8 122.0  82.2 110.4 106.1 107.6 118.8  94.7  98.1
## 133 1983  84.3  51.0  66.5  80.7  99.2  91.1  82.2  71.8  50.3  55.8  33.3
## 134 1984  57.0  85.4  83.5  69.7  76.4  46.1  37.4  25.5  15.7  12.0  22.8
## 135 1985  16.5  15.9  17.2  16.2  27.5  24.2  30.7  11.1   3.9  18.6  16.2
## 136 1986   2.5  23.2  15.1  18.5  13.7   1.1  18.1   7.4   3.8  35.4  15.2
## 137 1987  10.4   2.4  14.7  39.6  33.0  17.4  33.0  38.7  33.9  60.6  39.9
## 138 1988  59.0  40.0  76.2  88.0  60.1 101.8 113.8 111.6 120.1 125.1 125.1
## 139 1989 161.3 165.1 131.4 130.6 138.5 196.2 126.9 168.9 176.7 159.4 173.0
## 140 1990 177.3 130.5 140.3 140.3 132.2 105.4 149.4 200.3 125.2 145.5 131.4
## 141 1991 136.9 167.5 141.9 140.0 121.3 169.7 173.7 176.3 125.3 144.1 108.2
## 142 1992 150.0 161.1 106.7  99.8  73.8  65.2  85.7  64.5  63.9  88.7  91.8
## 143 1993  59.3  91.0  69.8  62.2  61.3  49.8  57.9  42.2  22.4  56.4  35.6
## 144 1994  57.8  35.5  31.7  16.1  17.8  28.0  35.1  22.5  25.7  44.0  18.0
## 145 1995  24.2  29.9  31.1  14.0  14.5  15.6  14.5  14.3  11.8  21.1   9.0
## 146 1996  11.5   4.4   9.2   4.8   5.5  11.8   8.2  14.4   1.6   0.9  17.9
## 147 1997   5.7   7.6   8.7  15.5  18.5  12.7  10.4  24.4  51.3  22.8  39.0
## 148 1998  31.9  40.3  54.8  53.4  56.3  70.7  66.6  92.2  92.9  55.5  74.0
## 149 1999  62.0  66.3  68.8  63.7 106.4 137.7 113.5  93.7  71.5 116.7 133.2
## 150 2000  90.1 112.9 138.5 125.5 121.6 124.9 170.1 130.5 109.7  99.4 106.8
## 151 2001  95.6  80.6 113.5 107.7  96.6 134.0  81.8 106.4 150.7 125.5 106.5
## 152 2002 114.1 107.4  98.4 120.7 120.8  88.3  99.6 116.4 109.6  97.5  95.5
## 153 2003  79.7  46.0  61.1  60.0  54.6  77.4  83.3  72.7  48.7  65.5  67.3
## 154 2004  37.3  45.8  49.1  39.3  41.5  43.2  51.1  40.9  27.7  48.0  43.5
## 155 2005  31.3  29.2  24.5  24.2  42.7  39.3  40.1  36.4  21.9   8.7  18.0
## 156 2006  15.3   4.9  10.6  30.2  22.3  13.9  12.2  12.9  14.4  10.5  21.4
## 157 2007  16.8  10.7   4.5   3.4  11.7  12.1   9.7   6.0   2.4   0.9   1.7
## 158 2008   3.3   2.1   9.3   2.9   3.2   3.4   0.8   0.5   1.1   2.9   4.1
## 159 2009   1.3   1.4   0.7   0.8   2.9   2.9   3.2   0.0   4.3   4.6   4.2
## 160 2010  13.2  18.8  15.4   8.0   8.7  13.6  16.1  19.6  25.2  23.5  21.6
##       Dec
## 1    71.4
## 2    45.4
## 3    23.4
## 4    21.6
## 5     3.1
## 6     7.2
## 7    37.2
## 8    66.9
## 9    81.0
## 10   95.6
## 11   80.5
## 12   40.9
## 13   41.2
## 14   28.6
## 15   12.8
## 16    1.5
## 17   25.2
## 18   67.6
## 19  104.3
## 20  130.0
## 21   90.4
## 22   83.9
## 23   49.2
## 24   29.3
## 25    9.9
## 26    8.2
## 27    2.2
## 28    0.5
## 29    7.3
## 30   29.6
## 31   47.3
## 32   41.8
## 33   75.9
## 34   47.2
## 35   21.7
## 36   13.0
## 37   20.7
## 38    6.7
## 39    6.7
## 40    7.8
## 41   32.5
## 42   78.6
## 43   93.8
## 44   60.0
## 45   70.7
## 46   42.6
## 47   33.3
## 48   12.6
## 49   10.5
## 50    0.3
## 51    0.0
## 52    1.1
## 53   45.6
## 54   54.6
## 55   55.5
## 56   64.7
## 57   47.3
## 58   39.5
## 59   54.2
## 60    5.8
## 61    2.2
## 62    6.4
## 63    3.8
## 64   22.3
## 65   34.5
## 66   53.0
## 67  129.3
## 68   59.2
## 69   34.9
## 70   29.9
## 71   20.3
## 72   17.5
## 73    2.8
## 74   16.5
## 75   98.6
## 76   79.4
## 77   45.2
## 78   59.0
## 79  108.0
## 80   25.8
## 81   17.8
## 82   11.0
## 83    0.3
## 84   15.4
## 85   61.5
## 86  123.4
## 87   88.8
## 88   92.7
## 89   42.1
## 90   68.3
## 91   33.7
## 92   22.5
## 93   18.8
## 94   28.4
## 95   27.4
## 96  121.7
## 97  116.5
## 98  138.0
## 99  117.6
## 100  54.1
## 101  45.8
## 102  34.3
## 103   2.5
## 104   7.6
## 105  76.9
## 106 192.1
## 107 239.4
## 108 187.6
## 109 125.0
## 110  85.6
## 111  39.9
## 112  23.2
## 113  14.9
## 114  15.1
## 115  17.0
## 116  70.4
## 117 126.4
## 118 109.8
## 119  97.9
## 120  83.5
## 121  82.2
## 122  45.3
## 123  23.3
## 124  20.5
## 125   7.8
## 126  15.3
## 127  43.2
## 128 122.7
## 129 176.3
## 130 174.4
## 131 150.1
## 132 127.0
## 133  33.4
## 134  18.7
## 135  17.3
## 136   6.8
## 137  27.1
## 138 179.2
## 139 165.5
## 140 129.7
## 141 144.4
## 142  82.6
## 143  48.9
## 144  26.2
## 145  10.0
## 146  13.3
## 147  41.2
## 148  81.9
## 149  84.6
## 150 104.4
## 151 132.2
## 152  80.8
## 153  46.5
## 154  17.9
## 155  41.1
## 156  13.6
## 157  10.1
## 158   0.8
## 159  10.6
## 160  14.5
  1. Create a histogram of the September sunspot numbers. (2)
library(ggplot2)
## Warning: package 'ggplot2' was built under R version 3.2.5
ggplot(SSN, aes(Sep)) + 
  geom_histogram(bins = 10)

  1. Create a box plot of the June sunspot numbers. Label the axis. (4)
boxplot(SSN$Jun)

ylab = "Sunspots in June"
  1. Create a scatter plot placing the June sunspot numbers on the horizontal axis and September sunspot numbers on the vertical axis. Label the axes. (4)
ggplot(SSN, aes(x = Jun, y = Sep)) +
  geom_point() + 
  xlab("Sunspots in June") + 
  ylab("Sunspots in September")

2 The babyboom dataset (UsingR) contains the time of birth, sex, and birth weight for 44 babies born in one 24-hour period at a hospital in Brisbane, Australia.

Create side-by-side box plots of birth weight (grams) by gender. Place the birth weight on the vertical axis and gender on the horizontal axis. (3)

3 The data set diamond (UsingR) contains data about the price of 48 diamond rings. The variable price records the price in Singapore dollars and the variable carat records the size of the diamond and you are interested in predicting price from carat size.

Make a scatter plot with carat on the horizontal axis and price on the vertical axis. (3)

4 The data frame homework (UsingR) contains the weekly average number of hours spent on homework for 15 private and 15 public schools.

  1. Use the function melt() from the reshape2 package to create a long data frame. (2)

  2. Use the long data frame and create side-by-side box plots of the hours spent on homework. (3)

5 Download and plot a road map of Sofia, Bulgaria. Use a zoom of 13. (7)