A DNP-NP is studying the health of a group of staff nurses at a large hospital and has collected the following data in an Excel spreadsheet dataset. The first page is the actual data which was collected, the second page provides the coding or key used for the variables. (In SPSS and EXCEL to analyze a set of data like this, all data has to be numerical, so we develop a way of coding variables which are measured in words, ie ordinal or nominal data, into numbers like this.)

Week 3 DataSet (Excel)

Using SPSS, calculate the means, medians, modes, range, standard deviation, skewness, and kurtosis for the variables which are measured in scale data. Use percentages to summarize any variables measured in nominal or ordinal level data. Calculate a 95% Confidence Interval for BMI.

ID AGE EDUCATION HEIGHT WEIGHT BMI BMIGROUP BPSYSTOLIC BPDIASTOLIC TEMPERATURE PULSE RESPIRATIONS EXERCISELEVEL SMOKINGHX DIABETES 1 20 1 66 120 19.4 1.0 155 122 98.6 65 16 2.0 0 0 2 20 1 68 160 24.4 1.0 176 143 98.9 70 15 3.0 1 1 3 25 1 64 145 25.0 2.0 151 118 97.2 85 19 2.0 0 1 4 33 1 72 220 29.9 2.0 192 159 97.6 110 22 2.0 0 0 5 48 1 67 250 39.3 4.0 92 59 99.6 105 23 0.0 1 1 6 27 1 74 230 29.6 2.0 163 130 98.1 107 24 2.0 1 1 7 31 1 75 190 23.8 1.0 157 124 97.9 59 14 4.0 1 1 8 58 1 61 110 20.8 1.0 184 151 97.8 57 13 3.0 0 1 9 64 1 60 150 29.4 2.0 189 156 98.6 97 18 2.0 0 0 10 26 1 61 125 23.7 1.0 189 156 98.3 64 20 2.0 1 1 11 38 1 68 148 22.6 1.0 104 71 99.2 81 17 3.0 0 0 12 46 1 63 139 24.7 1.0 166 133 99.3 90 16 3.0 1 1 13 51 1 66 142 23.0 1.0 167 134 98.6 73 15 3.0 1 1 14 42 1 65 175 29.2 2.0 112 79 97.1 101 23 2.0 0 1 15 30 1 69 189 28.0 2.0 149 116 97.4 92 21 3.0 0 1 16 22 1 70 215 30.9 3.0 174 141 98.1 98 22 1.0 0 1 17 27 1 64 115 19.8 1.0 99 66 98.9 62 14 3.0 0 0 18 23 1 65 146 24.4 1.0 109 76 100.3 73 16 3.0 1 0 19 35 1 66 157 25.4 2.0 174 141 97.9 86 20 2.0 0 1 20 53 1 59 120 24.3 1.0 195 161 98.9 78 15 2.0 0 1 21 65 1 77 220 26.2 2.0 107 73 98.6 82 22 2.0 0 0 22 68 1 54 95 23.0 1.0 93 62 99.4 91 18 3.0 0 0 23 69 1 64 150 25.8 2.0 119 85 97.5 71 22 2.0 0 0 24 20 1 62 175 32.1 3.0 97 63 98.5 55 15 1.0 1 1 25 27 1 52 180 46.9 5.0 176 142 99.0 76 12 1.0 1 1 26 55 1 66 130 21.0 1.0 176 142 99.2 97 13 3.0 0 1 27 62 1 70 195 28.1 2.0 118 84 99.1 69 15 2.0 0 0 28 59 1 63 124 22.0 1.0 113 79 98.8 79 20 3.0 1 0 29 21 1 56 109 24.5 1.0 118 84 98.7 99 23 3.0 1 1 30 69 1 70 230 33.1 3.0 175 141 98.4 63 12 0.0 1 1 31 45 1 54 115 27.8 2.0 159 125 97.4 57 20 2.0 0 1 32 38 1 79 245 27.7 2.0 89 61 97.1 50 20 2.0 1 0 33 32 1 67 250 39.3 4.0 138 104 98.2 96 24 0.0 1 0 34 56 1 72 350 47.6 5.0 155 121 98.1 50 16 0.0 1 1 35 35 1 76 276 33.7 3.0 186 152 98.0 83 24 2.0 1 1 36 58 1 66 130 21.0 1.0 107 73 99.0 76 12 3.0 0 0 37 60 1 76 196 23.9 1.0 169 135 99.4 61 23 3.0 0 0 38 42 1 73 205 27.1 2.0 136 102 99.0 55 18 2.0 0 0 39 58 1 69 210 31.1 3.0 183 149 99.2 76 21 1.0 0 0 40 55 1 53 160 40.2 5.0 190 156 98.6 55 26 1.0 1 1 41 55 1 51 118 32.0 3.0 101 67 98.1 90 12 1.0 1 1 42 59 1 53 134 33.6 3.0 114 80 98.2 81 19 1.0 1 0 43 46 1 77 220 26.2 2.0 92 60 98.9 84 20 2.0 0 0 44 44 1 72 260 35.4 4.0 140 106 98.8 49 18 0.0 1 1 45 38 1 78 300 34.8 3.0 104 68 97.8 73 16 2.0 0 0 46 59 1 66 180 29.1 2.0 185 149 97.9 57 13 2.0 1 0 47 59 1 65 140 23.4 1.0 142 106 97.6 64 22 3.0 0 0 48 23 1 69 140 20.7 1.0 148 112 98.0 76 15 3.0 1 0 49 53 1 69 176 26.1 2.0 138 102 97.3 90 12 2.0 0 0 50 54 1 78 200 23.2 1.0 140 104 98.4 99 17 2.0 0 0 51 20 1 78 235 27.2 2.0 108 72 97.1 75 21 2.0 0 1 52 35 1 75 215 26.9 2.0 166 130 99.0 58 21 2.0 0 0 53 47 1 59 124 25.1 2.0 135 99 99.6 59 12 2.0 0 1 54 37 1 62 143 26.2 2.0 105 69 99.8 70 13 2.0 0 0 55 63 1 66 160 25.9 2.0 106 70 100.0 73 16 3.0 0 0 56 56 1 63 110 19.5 1.0 91 59 101.2 75 25 3.0 0 0 57 38 1 61 108 20.5 1.0 161 125 98.6 56 22 3.0 0 1 58 34 1 57 131 28.4 2.0 169 133 98.5 61 16 2.0 0 1 59 62 1 68 164 25.0 2.0 174 138 98.4 49 19 2.0 1 1 60 56 2 63 119 21.1 1.0 139 103 98.3 83 18 2.0 0 0 61 35 2 61 136 25.8 2.0 178 142 97.9 69 13 2.0 0 0 62 60 2 52 176 45.9 5.0 85 59 97.6 56 13 0.0 1 1 63 42 2 64 138 23.8 1.0 98 62 97.8 70 15 3.0 1 1 64 38 2 50 97 27.4 2.0 116 80 98.1 64 20 2.0 1 0 65 48 2 68 185 28.2 2.0 139 103 98.5 68 15 3.0 0 1 66 41 2 70 189 27.2 2.0 129 93 99.6 55 18 2.0 0 1 67 24 2 54 127 30.7 3.0 117 81 99.7 50 15 1.0 0 0 68 70 2 64 134 23.1 1.0 120 84 101.1 58 21 3.0 1 0 69 68 2 53 106 26.6 2.0 102 66 100.1 89 14 2.0 0 0 70 44 2 79 210 23.7 1.0 100 64 97.4 99 20 2.0 1 0 71 61 2 79 246 27.8 2.0 133 97 98.2 102 20 2.0 0 1 72 24 2 66 172 27.8 2.0 149 113 98.5 99 20 2.0 1 0 73 33 2 70 200 28.8 2.0 180 144 98.9 53 19 2.0 1 0 74 59 2 60 118 23.1 1.0 165 129 97.2 86 14 3.0 1 0 75 63 2 80 248 27.3 2.0 109 73 97.4 88 15 3.0 1 1 76 57 2 58 128 26.8 2.0 170 134 98.6 87 22 2.0 1 0 77 24 2 54 107 25.9 2.0 150 114 98.2 66 23 2.0 0 0 78 34 2 62 104 19.1 1.0 150 114 98.9 67 20 3.0 0 0 79 27 2 64 149 25.6 2.0 110 74 99.5 85 16 2.0 0 0 80 51 2 69 150 22.2 1.0 143 107 99.3 68 20 2.0 1 1 81 27 2 79 205 23.2 1.0 87 56 97.3 84 19 3.0 0 0 82 49 2 75 234 29.3 2.0 99 63 97.5 100 15 2.0 0 1 83 20 2 63 132 23.4 1.0 93 57 98.3 69 17 3.0 0 1 84 43 2 71 212 29.6 2.0 100 64 98.4 71 18 2.0 0 0 85 41 2 57 113 24.5 1.0 151 115 99.1 97 14 4.0 0 1 86 49 3 56 138 31.0 3.0 188 152 98.6 52 19 1.0 0 0 87 31 3 52 130 33.9 3.0 105 69 97.4 64 13 1.0 0 1 88 28 3 69 207 30.7 3.0 106 70 97.9 52 17 1.0 0 0 89 37 3 66 140 22.7 1.0 191 155 97.3 84 16 3.0 1 0 90 43 3 56 106 23.8 1.0 109 73 97.8 59 16 2.0 1 0 91 44 3 75 227 28.5 2.0 138 102 98.5 60 14 2.0 0 1 92 57 3 73 238 31.5 3.0 173 137 98.7 57 14 1.0 1 0 93 50 3 62 119 21.8 1.0 189 153 98.2 77 12 3.0 0 0 94 36 3 56 128 28.8 2.0 173 137 99.6 101 20 2.0 1 0 95 44 3 50 106 29.9 2.0 131 95 99.9 85 18 3.0 1 0 96 21 3 63 133 23.6 1.0 120 84 101.5 91 16 3.0 0 1 97 57 3 79 325 36.7 4.0 142 106 102.0 67 23 0.0 1 0 98 27 3 67 215 33.8 3.0 95 65 98.6 53 20 1.0 1 1 99 67 3 50 164 46.2 5.0 176 143 98.4 58 19 0.0 1 1 100 22 3 56 189 42.5 5.0 133 81 98.3 83 15 1.0 1 1