A health researcher wants to be able to predict whether the incidence of heart disease can be predicted based on age, weight, gender and maximal aerobic capacity (VO₂max) (an indicator of fitness and health). To this end, the researcher recruited 100 participants to perform a maximum VO₂max test as well as recording their age, weight and gender. The participants were also evaluated for the presence of heart disease. Run a logistic regression to determine whether the presence of heart disease could be predicted from their VO₂max, age, weight and gender. Note: this data is fictitious. Give your answer showing the output from SPSS and your interpretation. the below columns are Case#, age, weight, gender, Vo2max, heart disease (from SPSS)

1 37 70.47 1.00 55.79 .00 3 46 87.65 1.00 42.93 1.00 4 36 89.80 .00 28.30 1.00 5 34 103.02 1.00 40.56 .00 6 39 77.37 .00 33.00 .00 7 34 82.48 1.00 43.48 .00 8 37 75.94 .00 30.38 .00 9 35 97.11 1.00 40.17 1.00 10 32 78.42 .00 36.01 .00 11 40 88.02 1.00 44.22 1.00 12 55 74.47 .00 38.76 1.00 13 35 75.98 .00 33.09 .00 14 46 58.97 .00 44.81 .00 15 33 111.80 1.00 31.94 .00 16 39 79.81 .00 34.48 .00 17 47 56.18 1.00 47.23 1.00 18 40 86.13 1.00 45.06 .00 19 46 87.30 1.00 55.12 .00 20 46 88.52 1.00 45.58 1.00 21 36 68.52 .00 37.52 .00 22 41 76.70 .00 36.27 .00 23 40 62.51 1.00 62.50 .00 24 34 60.90 .00 37.09 .00 25 36 53.43 1.00 44.27 1.00 26 33 68.52 .00 40.34 .00 27 55 72.37 1.00 55.19 1.00 28 48 82.16 .00 49.87 .00 29 40 90.92 1.00 38.06 1.00 30 31 95.51 1.00 48.13 .00 31 49 73.14 .00 42.42 1.00 32 36 62.59 1.00 48.23 1.00 33 38 91.38 1.00 42.96 1.00 34 51 94.29 1.00 42.53 1.00 35 50 58.07 1.00 40.90 .00 36 35 90.25 .00 27.35 .00 37 31 78.45 .00 38.70 .00 38 32 74.78 1.00 62.13 .00 39 43 85.13 1.00 45.69 .00 40 38 101.25 1.00 40.73 1.00 41 31 58.94 1.00 41.82 .00 42 47 101.06 1.00 35.60 1.00 43 31 97.75 1.00 42.20 .00 44 32 72.50 1.00 45.30 .00 45 37 88.45 1.00 40.02 1.00 46 34 72.29 1.00 47.17 .00 47 41 94.59 1.00 44.43 1.00 48 38 115.42 1.00 38.12 .00 49 40 51.96 .00 50.05 .00 50 41 89.35 1.00 48.64 .00 51 43 62.01 .00 36.49 .00 52 33 68.03 1.00 61.71 .00 53 39 79.39 .00 33.84 .00 54 35 81.91 .00 51.20 .00 55 42 64.00 .00 35.00 1.00 56 39 59.78 .00 47.71 .00 57 31 71.03 1.00 52.30 .00 58 44 50.00 .00 42.00 .00 60 41 112.59 1.00 37.34 1.00 61 74 73.38 .00 40.58 1.00 62 36 62.85 1.00 60.55 .00 63 55 68.29 .00 37.93 1.00 64 31 94.68 1.00 44.94 .00 65 38 103.23 1.00 35.01 1.00 66 55 81.01 1.00 45.57 .00 67 32 69.02 .00 36.63 .00 68 30 55.00 .00 60.00 .00 69 32 73.44 .00 40.52 .00 71 48 85.94 1.00 45.84 .00 72 40 64.65 1.00 60.92 .00 73 62 88.83 1.00 32.00 1.00 74 32 82.41 1.00 49.40 .00 75 33 63.00 .00 50.00 .00 76 63 78.67 .00 31.99 .00 77 43 95.10 1.00 39.90 1.00 78 51 87.05 1.00 47.16 .00 79 32 69.97 1.00 61.76 .00 80 36 90.63 .00 33.58 .00 81 42 92.43 1.00 47.26 .00 82 37 79.31 1.00 54.67 .00 83 33 80.61 1.00 49.68 .00 84 41 74.87 1.00 50.19 1.00 85 34 101.62 1.00 36.19 .00 86 35 74.70 1.00 57.64 .00 87 63 87.28 1.00 49.87 .00 88 43 72.57 .00 34.85 .00 89 42 75.82 .00 33.67 1.00 90 43 53.00 .00 42.00 .00 91 34 75.15 1.00 58.32 .00 92 50 103.53 1.00 45.23 1.00 93 33 79.65 .00 30.37 .00 94 36 70.84 1.00 55.91 .00 95 48 79.17 1.00 49.42 .00 96 42 111.98 1.00 33.73 1.00 97 43 88.07 1.00 49.22 1.00 98 45 94.07 1.00 41.97 1.00 99 58 97.46 1.00 35.20 1.00 100 61 93.76 1.00 32.00 1.00