In a chemical engineering experiment dealing with heat transfer in a shallow fluidized bed, data are collected on the following four regressor variables: fluidizing gas flow rate, lb/hr (x₁); supernatant gas flow rate, lb/hr (x₂); supernatant gas inlet nozzle opening, millimeters (as); supernatant gas inlet temperature, ?F (x₄). The responses measured are heat transfer efficiency (y₁): thermal efficiency (y₂). The data are as follows. Consider the model for predicting the heat transfer co-efficient response

(a) Compute PRESS and ? ^n?_i=1? y i ? y i,-i? for the least squares regression fit to the model above,

(b) Fit a second-order model with x4 completely eliminated (i.e., deleting all terms involving ?1). Compute the prediction criteria for the reduced model. Comment on the appropriateness of x4 for prediction of the heat transfer coefficient.

(c) Repeat parts (a) and (b) for thermal efficiency

Transcribed Image Text:

Obs. 12 22 41.852 38.75 69.69 170.83 45 219.74 2 155.329 51.87 113.46 230.06 25 181.22 99.628 53.79 113.54 228.19 65 179.06 49.409 53.84 118.75 117.73 65 281.30 72.958 49.17 119.72 117.69 25 282.20 107.702 47.6i 168.38 173.46 45 216.14 97.239 64.19 169.85 169.85 45 223.88 105.856 52.73 169.85 170.86 45 222.80 99.348 51.00 170.89 173.92 80 218.84 10 111.907 47.37 171.31 100.008 43.18 171.43 171.43 45 219.20 12 175.380 71.23 171.59 263.49 45 168.62 4 6. 173.34 25 218.12 11 13 117.800 49.30 171.63 171.63 45 217.58 219.92 14 217.409 50.87 171.93 170.91 10 71.73 45 296.60 217.39 65 41.725 54.44 173.92 15 47.93 221.44 189.14 16 151.139 17 220.630 42.91 222.74 186.08 221.73 25 18 131.666 66.60 228.90 19 285.80 114.40 25 113.52 65 286.34 64.94 231.19 80.537 221.72 43.18 236.84 20 152.966 167.77 45 ΣΒΕ-Σ, η 2B,#;;+ yıi =00 + j=1 +2B1*jian+ €i, = 1.2... 20.