Can I get help on this Linear Regression homework? And is it possible to have it back by 11:45PM, MST tonight?

Doc attached.

Thanks, Carrol

I tried attaching the doc.....let me do a screen shot - data is on tab #2 - is there anyway to attach the Excel doc?

Name Carrol Lee Rideshare data On the next tab you will find data the the following variables Y X1 X2 X3 X4 X5 Fuel Weather Distance Traffic Load Passengers Present your Full Model Rsq Standard error Best predictor of Trip price Weakest predictor of price Are the regression coeficents in the direction you would expect (Y/N) Fuel (Y/N) Weather (Y/N) Distance (Y/N) Traffic Load Passengers you will find data the the following variables Price - Fare on a rideshare (Uber, Lyft.....) Fuel - Fuel Price at the time Weather - Weather conditions at the time - Clear=3, Fog=2, Wet=1 Distance - Distance in miles Traffic Load - Hi/Lo traffic periods - Hi=1, Lo=0 (binary) Passengers - Number of Passenger on trip Interpret each regression coefficent relative trip price For example, each additional passenger (Increases,Decreases) trip price by xx.xx nt your Full Model redictor of Trip price est predictor of price e regression coeficents in the direction you would expect (Y/N) For example, one might expect increases in fuel prices will increase trip prices - Yes Tasks to complete assignment on the ne YOU DO NOT NEED TO RUN RE 1. Determine the means and s 2. Present the Correlation Tab 3. Develop the (full) Multiple R 4. Complete the items on the mplete assignment on the next tab YOU DO NOT NEED TO RUN REDUCED MODELS AS I ILLUSTRATED IN THE XLMiner VIDEO 1. Determine the means and standard deviations for the Ride Share data 2. Present the Correlation Table for the Ride Share data 3. Develop the (full) Multiple Regression model of Price against Fuel, Weather, Distance, Traffic Load and Passengers 4. Complete the items on the left Y Price 6.8 10.3 7.3 12.6 7.7 11.9 8.7 10.4 12.3 11.2 9.0 13.5 13.0 10.1 8.5 6.9 10.9 10.3 6.4 10.2 7.3 8.5 13.4 7.8 11.5 10.0 9.8 11.2 12.3 11.1 X1 X2 X3 X4 Fuel Weather Distance Traf load 2.19 2.00 0.92 0 2.60 3.00 3.75 1 2.18 1.00 3.68 0 3.00 1.00 5.10 1 2.00 1.00 3.36 0 2.80 1.00 4.84 1 2.16 2.00 3.04 0 2.64 1.00 3.64 1 2.49 1.00 4.17 1 2.59 1.00 4.38 1 2.70 2.00 3.31 0 2.85 2.00 3.76 1 2.51 1.00 4.17 1 2.68 1.00 2.94 1 2.15 1.00 4.45 0 2.29 1.00 2.73 0 2.42 2.00 4.54 1 2.60 1.00 3.40 1 2.40 2.00 1.81 0 2.60 1.00 2.67 1 2.05 1.00 2.59 0 2.21 2.00 3.79 0 2.69 1.00 5.35 1 2.16 1.00 2.53 0 2.71 3.00 3.11 1 3.03 3.00 3.67 1 2.51 1.00 3.91 0 2.34 1.00 4.93 1 2.65 1.00 4.66 1 2.36 2.00 3.55 1 X5 Pass 3 1 1 1 2 2 2 1 1 1 3 2 2 1 1 1 3 1 1 1 1 2 3 1 1 1 2 1 1 2 Stack your analysis below - (Means, Standard Deviations), (Correlations), (Regression Models) Price Means Standard Deviations Correlation Matrix Regression Models Fuel Weather Distance Traf load 8.1 7.2 8.4 8.7 3.4 11.7 7.5 12.1 9.9 9.7 7.4 12.6 8.9 8.5 9.5 7.6 8.2 11.9 9.0 10.6 12.3 9.9 7.9 7.8 10.3 10.0 7.9 10.6 9.1 10.0 9.9 11.5 2.31 1.93 2.25 2.28 1.79 3.03 2.17 2.78 2.52 2.28 2.67 2.94 2.87 2.63 2.43 2.63 2.54 2.41 2.39 2.12 2.22 2.70 2.60 2.41 2.72 2.59 2.40 2.55 2.16 2.62 2.31 2.54 1.00 3.00 1.00 2.00 1.00 1.00 3.00 2.00 1.00 1.00 1.00 2.00 2.00 2.00 1.00 1.00 1.00 2.00 1.00 1.00 1.00 2.00 2.00 1.00 1.00 2.00 2.00 1.00 1.00 2.00 1.00 2.00 3.56 1.98 3.59 3.59 0.65 4.10 3.11 3.93 3.37 3.53 2.73 5.25 2.16 3.04 2.69 3.65 3.63 4.86 3.34 3.57 4.90 4.67 2.91 2.15 3.84 2.79 2.16 3.48 2.82 4.10 2.70 4.49 0 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0 1 0 1 1 0 0 0 1 0 0 1 0 1 0 1 1 1 2 2 1 2 1 2 2 2 2 2 1 1 2 1 2 1 1 2 2 1 1 2 1 1 2 1 1 3 1 2 10.8 11.8 9.9 9.3 10.4 9.4 8.4 11.4 12.0 9.2 13.0 10.6 10.4 11.6 7.6 9.3 7.5 9.5 6.2 12.6 8.0 9.4 11.7 10.4 5.2 8.8 11.8 11.6 7.8 10.9 11.2 13.4 2.62 2.73 2.55 2.23 2.37 2.58 2.27 2.57 2.87 2.07 3.14 2.49 2.29 2.62 2.75 2.50 2.42 2.79 1.90 2.41 2.70 2.60 3.02 2.62 2.52 2.34 2.94 2.31 2.55 2.86 2.42 2.85 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 2.00 3.00 1.00 2.00 2.00 1.00 2.00 1.00 2.00 1.00 1.00 2.00 1.00 1.00 1.00 3.00 3.00 1.00 2.00 2.00 2.00 1.00 3.28 5.25 3.59 3.57 3.73 3.11 4.08 3.93 5.60 2.42 4.34 3.34 3.42 3.55 2.34 3.25 2.14 3.54 1.37 4.37 2.97 3.71 4.99 3.29 1.79 1.50 3.11 3.65 2.66 3.23 3.82 4.67 1 1 0 0 1 0 0 1 1 0 1 1 1 1 0 0 0 0 0 1 0 0 1 1 0 0 1 1 0 1 1 1 2 2 1 1 2 1 2 1 1 1 1 1 1 1 2 1 1 2 2 1 1 1 1 1 1 1 1 1 1 2 3 2 9.0 6.4 11.8 11.7 10.0 9.7 11.8 12.0 4.0 7.4 11.0 9.9 12.3 9.1 7.4 8.8 10.6 12.4 9.2 11.3 9.9 6.4 10.8 7.7 14.6 13.0 11.4 7.3 9.6 11.2 7.7 11.9 2.49 2.44 2.37 2.56 2.61 2.68 2.53 2.55 2.00 2.51 2.40 2.36 2.47 2.30 2.36 2.18 2.51 2.83 2.40 2.52 2.67 2.36 2.61 2.86 2.93 3.14 2.31 2.25 2.25 2.30 2.56 2.55 2.00 1.00 1.00 1.00 2.00 1.00 1.00 1.00 1.00 3.00 1.00 1.00 1.00 1.00 1.00 2.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 2.00 1.00 2.00 1.00 2.00 1.00 1.00 1.00 2.82 1.70 2.93 4.37 3.65 1.38 4.43 4.64 0.63 2.40 3.71 3.66 4.33 2.28 2.35 2.49 3.15 3.42 2.31 4.33 3.04 2.47 4.09 2.88 4.94 5.04 5.30 2.24 3.02 4.23 2.67 3.65 0 0 1 1 0 0 1 1 0 0 1 0 1 0 0 0 1 1 0 1 0 0 1 0 1 1 1 0 0 1 0 1 1 1 2 2 1 2 2 1 1 2 2 1 2 2 2 1 2 1 1 1 1 1 1 1 1 2 1 2 1 1 2 1 15.3 10.7 9.1 10.3 10.2 10.2 8.8 8.1 11.9 8.9 13.8 9.1 8.9 7.9 11.2 11.4 9.2 10.8 9.0 12.4 13.0 13.6 7.4 8.0 12.4 9.4 14.0 10.3 9.6 12.6 10.8 9.9 2.68 2.79 2.48 2.80 2.15 2.34 2.65 2.24 2.59 2.29 3.01 2.39 2.39 2.68 2.55 2.12 2.24 2.60 2.09 2.63 2.59 2.85 2.39 2.44 2.59 2.40 2.46 2.33 2.32 2.69 2.47 2.60 1.00 1.00 1.00 2.00 1.00 1.00 1.00 2.00 1.00 1.00 1.00 2.00 1.00 1.00 1.00 1.00 1.00 2.00 2.00 1.00 2.00 2.00 1.00 1.00 2.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 5.63 4.30 3.33 4.06 2.82 3.82 4.06 3.47 3.69 3.01 5.08 3.13 4.39 2.73 4.66 4.26 4.08 3.78 3.04 4.24 4.65 4.57 1.16 2.39 4.18 3.05 5.58 3.93 2.73 3.55 3.97 3.35 1 1 0 1 1 1 0 0 1 0 1 0 0 0 1 1 0 1 0 1 1 1 0 0 1 0 1 1 0 1 1 0 1 1 2 1 1 1 1 2 2 1 1 1 2 1 1 1 1 1 1 2 1 1 1 1 2 1 1 1 2 1 3 2 11.5 7.2 12.6 6.9 8.6 10.3 10.5 9.9 7.6 11.2 13.0 12.0 10.2 12.3 6.9 12.0 12.1 11.1 12.8 11.3 9.6 11.4 7.1 10.8 8.3 6.0 9.0 10.1 11.8 10.1 9.2 10.2 2.47 2.66 3.04 2.33 2.26 2.72 2.63 2.71 2.69 2.49 2.24 2.57 2.74 2.86 2.13 2.63 2.58 2.66 2.71 2.67 2.09 2.57 2.16 2.26 2.21 2.32 2.20 2.31 2.20 2.32 2.56 2.29 1.00 1.00 1.00 1.00 1.00 2.00 2.00 1.00 2.00 1.00 1.00 3.00 1.00 2.00 1.00 2.00 1.00 1.00 1.00 1.00 2.00 1.00 1.00 1.00 2.00 2.00 2.00 1.00 1.00 1.00 1.00 1.00 3.35 2.80 3.60 1.57 2.79 3.86 2.64 4.20 2.00 4.14 5.08 3.61 3.41 4.94 1.61 4.75 5.38 4.40 4.99 3.74 4.48 4.59 1.06 3.37 2.99 2.14 3.37 4.38 3.77 3.03 2.99 3.93 1 0 1 0 0 1 1 0 0 1 1 1 1 1 0 1 1 1 1 1 0 1 0 1 0 0 0 1 1 1 0 1 2 1 2 1 2 1 1 1 1 2 2 2 1 1 1 1 2 1 1 3 2 1 1 2 1 1 2 1 2 3 2 1 10.0 7.9 10.9 9.6 9.4 11.1 10.0 10.2 12.0 9.4 2.17 2.26 2.69 2.50 2.63 2.72 2.91 2.56 2.61 2.78 1.00 2.00 1.00 1.00 1.00 2.00 2.00 1.00 2.00 1.00 3.77 3.10 3.97 3.34 3.11 3.92 4.26 2.36 4.58 3.73 0 0 1 0 0 1 1 1 1 0 1 2 1 2 2 1 1 2 2 2 elations), (Regression Models) Pass