Question
The Springdata sample data is a weather record for the month of April. The variable Precip measures rainfall. Added a column named Rained to categorize
The Springdata sample data is a weather record for the month of April. The variable Precip measures rainfall. Added a column named "Rained" to categorize rainfall using a formula.
The condition is that if Precip > 2, then "Rain", else "Dry"
1.Generate a histogram and a frequency table of the Rained variable. From this cart, what is the probability of Rain in the month of April?
2. We want to increase the probability of correct predictions by including other variables. Specifically, we want to use morning temperature or barometric pressure to help make more informed predictions. Use the Analyze > Fit Y by X platform to show cumulative plots for each of the two cases. Also show the logistics regression tables each case.
3.Using the plots and the tables, draw your conclusions on which of the two factors help(s) in predicting whether or not it rains in April.
Month # | Month | Date | Temp | April | Humid1:PM | Humid4:PM | Precip | Pressure | wrDIR1:PM | wDIR4:PM | wrSpeed | SkyCover | Rained |
4 | APR | 1-Apr | 39 | 1 | 30 | 28 | 0 | 29.6 | 27 | 28 | 4.5 | 0 | Dry |
4 | APR | 2-Apr | 53 | 2 | 32 | 29 | 0 | 29.51 | 20 | 29 | 10.7 | 6 | Dry |
4 | APR | 3-Apr | 50 | 3 | 53 | 86 | 0.27 | 29.4 | 7 | 86 | 6.8 | 8 | Rainy |
4 | APR | 4-Apr | 43 | 4 | 47 | 42 | 0.05 | 29.21 | 25 | 42 | 14.2 | 10 | Rainy |
4 | APR | 5-Apr | 42 | 5 | 44 | 48 | 0.001 | 29.32 | 27 | 48 | 9.7 | 8 | Dry |
4 | APR | 6-Apr | 46 | 6 | 42 | 41 | 0.001 | 29.33 | 29 | 41 | 10.5 | 7 | Dry |
4 | APR | 7-Apr | 52 | 7 | 40 | 37 | 0 | 29.3 | 27 | 37 | 8.8 | 3 | Dry |
4 | APR | 8-Apr | 59 | 8 | 36 | 23 | 0 | 29.31 | 30 | 23 | 6.7 | 3 | Dry |
4 | APR | 9-Apr | 56 | 9 | 31 | 25 | 0 | 29.33 | 34 | 25 | 3.3 | 3 | Dry |
4 | APR | 10-Apr | 57 | 10 | 27 | 23 | 0 | 29.41 | 22 | 23 | 1.1 | 0 | Dry |
4 | APR | 11-Apr | 62 | 11 | 42 | 43 | 0.08 | 29.36 | 17 | 43 | 6.3 | 8 | Rainy |
4 | APR | 12-Apr | 66 | 12 | 45 | 66 | 0.23 | 29.38 | 22 | 66 | 6.8 | 8 | Rainy |
4 | APR | 13-Apr | 61 | 13 | 35 | 31 | 0 | 29.58 | 34 | 31 | 3.6 | 2 | Dry |
4 | APR | 14-Apr | 58 | 14 | 58 | 52 | 0.001 | 29.71 | 11 | 52 | 9.6 | 10 | Dry |
4 | APR | 15-Apr | 58 | 15 | 93 | 90 | 2.14 | 29.4 | 12 | 90 | 12.8 | 10 | Rainy |
4 | APR | 16-Apr | 61 | 16 | 76 | 46 | 0.97 | 29.08 | 15 | 46 | 3 | 9 | Rainy |
4 | APR | 17-Apr | 57 | 17 | 56 | 58 | 0.12 | 29.11 | 17 | 58 | 2.2 | 10 | Rainy |
4 | APR | 18-Apr | 57 | 18 | 90 | 93 | 0.09 | 29.33 | 1 | 93 | 7.9 | 10 | Rainy |
4 | APR | 19-Apr | 63 | 19 | 76 | 70 | 0.001 | 29.51 | 1 | 70 | 10.4 | 9 | Dry |
4 | APR | 20-Apr | 65 | 20 | 55 | 50 | 0 | 29.56 | 2 | 50 | 9.8 | 6 | Dry |
4 | APR | 21-Apr | 65 | 21 | 61 | 57 | 0.001 | 29.53 | 36 | 57 | 7.8 | 8 | Dry |
4 | APR | 22-Apr | 68 | 22 | 38 | 37 | 0 | 29.51 | 6 | 37 | 3.1 | 5 | Dry |
4 | APR | 23-Apr | 64 | 23 | 76 | 71 | 0.001 | 29.53 | 9 | 71 | 6.7 | 10 | Dry |
4 | APR | 24-Apr | 63 | 24 | 93 | 93 | 0.71 | 29.34 | 12 | 93 | 3.6 | 10 | Rainy |
4 | APR | 25-Apr | 53 | 25 | 83 | 86 | 0.02 | 29.52 | 3 | 86 | 13.8 | 10 | Dry |
4 | APR | 26-Apr | 54 | 26 | 46 | 27 | 0.001 | 29.67 | 1 | 27 | 12.5 | 4 | Dry |
4 | APR | 27-Apr | 55 | 27 | 24 | 23 | 0 | 29.64 | 3 | 23 | 2 | 3 | Dry |
4 | APR | 28-Apr | 57 | 28 | 27 | 23 | 0 | 29.47 | 33 | 23 | 7 | 4 | Dry |
4 | APR | 29-Apr | 57 | 29 | 22 | 22 | 0 | 29.45 | 24 | 22 | 10.5 | 0 | Dry |
4 | APR | 30-Apr | 72 | 30 | 32 | 30 | 0 | 29.33 | 26 | 30 | 4.6 | 3 | Dry |
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