Question

Please DONT ANSWER if you're UNSURE, because this is LAST QUESTION that i can ask on chegg. Really appreciate your effort and understanding.

Below is the output table for the regression model used to predict daily check-ins. Don't be intimidated by the size of the output. Even though there are a lot of variables, the process for analyzing this output is the same as it was when we had two or three independent variables. SUMMARY OUTPUT Dependent Variable: Checkins Regression Statistics Multiple R 0.6456 R Square 0.4168 Adjusted R Square 0.3994 Standard Error 316.70 Observations 1,309 ANOVA Significance F 0.0000 Regression Residual of 38 1,270 1,308 Coefficients -163.90 Total Lower 95% -491.53 Upper 95% 163.74 (Intercept) PayDay 96.68 SSM S F 9.10E+07 2.40E+06 23.97 1.27E+06 1.00E+05 2.18E+08 Standard Error Stat P-value 167.00 -0.98 0.3266 35.91 2.690.0072 192.26 -3.38 0.0008 160.58 0.0000 165.35 0.0000 161.97 0.0063 63.79 0.0059 161.74 26.22 167.14 New Years -649.04 - 1,026.22 -271.87 Martin Lutherking 862.09 547.06 1.177.13 -679.67 - 1,004.05 SuperBowl Valentines Day -443.61 -761.38 -365.29 - 125.85 300.95 Chinese New Year 175.81 2.78 50.67 PresidentsDay 1,303.94 8.06 986.63 1,621.26 Easter -234.93 7:38 0.1679 -568.98 170.28 58.81 99.13 Passover -4.74 -0.08 0.9358 - 120.11 MothersDay 19.93 0.9014 -295.75 Memorial Day 160.91 161.07 160.99 -90.40 0.1616 0.6830 Fathers Day 110.63 335.62 541.59 250.07 -23.02 382.11 225.80 -65.76 -338.44 16.67 -381.59 1.40 -0.41 -2.11 0.09 July4th -653.85 180.77 186.27 0.0356 0.9287 Labor Day -348.76 Fathers Day -65.76 160.99 -0.41 0.6830 -381.59 250.07 -23.02 July4th - 653.85 -338.44 16.67 160.77 186.27 0.0356 0.9287 Labor Day -348.76 382.11 0.09 0.72 RoshHashanah 78.09 -113.36 108.33 130.28 0.4712 0.3844 - 134.44 -368.95 290.62 142.23 Yomkippur Columbus Day 185.06 -0.26 0.7971 Halloween 183.55 0.1006 - 47.59 -301.57 56.98 79.32 -410.85 -661.87 -303.59 -286.04 Veterans Day 183.79 315.47 58.52 417.56 444.88 89.62 Thanksgiving 186.23 0.7566 0.6702 0.5709 0.43 Chanukah 64.25 - 162.45 Christmas -308.66 188.71 61.56 Sunday 35.77 -1.84 15.70 8.97 0.1022 0.0000 0.0000 -678.88 491.55 206.97 Monday 288.05 Tuesday 29 88.89 13.96 0.0221 0.0005 Wednesday 145.22 3.52 64.20 631.89 369.13 179.81 226.24 340.90 669.54 224.27 Thursday 266.61 7.04 0.0000 192.31 Friday 540.24 2010 19 2011 2012 38.41 29.01 0.07 0.0000 0.0001 0.0000 0.0000 0.0001 0.0092 73.23 123.92 167.35 0.15 TotalRewards 4.05 Special Event 0.07 0.05 VIP 0.00 -7.77 0.0777 Freelndependent 6.60 0.0000 Wholesale 1.12 0.2618 -0.35 0.28 -0.00 0.17 -0.81 0.32 0.35 Group 0.26 -0.42 0.05 0.20 5.73 -2.08 0.0000 0.0379 Rate -0.02 Shared Reflection Recall your hypotheses about the impact of the independent variables on the number of daily check-ins. Are there any coefficients that surprise you or contradict your original hypotheses? Develop a possible explanation for why the estimated coefficients might make sense in the context of the problem Do the coefficients for payday or any of the holidays surprise you? What was your original hypothesis for those variables? Interpret the coefficients and explain why they support or contradict your intuition. Do any of the coefficients for day of the week surprise you? What was your original hypothesis for those variables? Interpret the coefficients and explain why they support or contradict your intuition. Do any of the coefficients for the number of rooms reserved on a given day to a particular type of guest (TotalRewards, Special Event, VIP, FreeIndependent, Wholesale, Group) surprise you? What was your original hypothesis for those variables? Interpret the coefficients and explain why they support or contradict your intuition. Does the coefficient Rate surprise you? What was your original hypothesis for that variable? Interpret the coefficient and explain why it supports or contradicts your intuition. MINIMUM MAXIMUM Words 1000 50 Enter your reflection Below is the output table for the regression model used to predict daily check-ins. Don't be intimidated by the size of the output. Even though there are a lot of variables, the process for analyzing this output is the same as it was when we had two or three independent variables. SUMMARY OUTPUT Dependent Variable: Checkins Regression Statistics Multiple R 0.6456 R Square 0.4168 Adjusted R Square 0.3994 Standard Error 316.70 Observations 1,309 ANOVA Significance F 0.0000 Regression Residual of 38 1,270 1,308 Coefficients -163.90 Total Lower 95% -491.53 Upper 95% 163.74 (Intercept) PayDay 96.68 SSM S F 9.10E+07 2.40E+06 23.97 1.27E+06 1.00E+05 2.18E+08 Standard Error Stat P-value 167.00 -0.98 0.3266 35.91 2.690.0072 192.26 -3.38 0.0008 160.58 0.0000 165.35 0.0000 161.97 0.0063 63.79 0.0059 161.74 26.22 167.14 New Years -649.04 - 1,026.22 -271.87 Martin Lutherking 862.09 547.06 1.177.13 -679.67 - 1,004.05 SuperBowl Valentines Day -443.61 -761.38 -365.29 - 125.85 300.95 Chinese New Year 175.81 2.78 50.67 PresidentsDay 1,303.94 8.06 986.63 1,621.26 Easter -234.93 7:38 0.1679 -568.98 170.28 58.81 99.13 Passover -4.74 -0.08 0.9358 - 120.11 MothersDay 19.93 0.9014 -295.75 Memorial Day 160.91 161.07 160.99 -90.40 0.1616 0.6830 Fathers Day 110.63 335.62 541.59 250.07 -23.02 382.11 225.80 -65.76 -338.44 16.67 -381.59 1.40 -0.41 -2.11 0.09 July4th -653.85 180.77 186.27 0.0356 0.9287 Labor Day -348.76 Fathers Day -65.76 160.99 -0.41 0.6830 -381.59 250.07 -23.02 July4th - 653.85 -338.44 16.67 160.77 186.27 0.0356 0.9287 Labor Day -348.76 382.11 0.09 0.72 RoshHashanah 78.09 -113.36 108.33 130.28 0.4712 0.3844 - 134.44 -368.95 290.62 142.23 Yomkippur Columbus Day 185.06 -0.26 0.7971 Halloween 183.55 0.1006 - 47.59 -301.57 56.98 79.32 -410.85 -661.87 -303.59 -286.04 Veterans Day 183.79 315.47 58.52 417.56 444.88 89.62 Thanksgiving 186.23 0.7566 0.6702 0.5709 0.43 Chanukah 64.25 - 162.45 Christmas -308.66 188.71 61.56 Sunday 35.77 -1.84 15.70 8.97 0.1022 0.0000 0.0000 -678.88 491.55 206.97 Monday 288.05 Tuesday 29 88.89 13.96 0.0221 0.0005 Wednesday 145.22 3.52 64.20 631.89 369.13 179.81 226.24 340.90 669.54 224.27 Thursday 266.61 7.04 0.0000 192.31 Friday 540.24 2010 19 2011 2012 38.41 29.01 0.07 0.0000 0.0001 0.0000 0.0000 0.0001 0.0092 73.23 123.92 167.35 0.15 TotalRewards 4.05 Special Event 0.07 0.05 VIP 0.00 -7.77 0.0777 Freelndependent 6.60 0.0000 Wholesale 1.12 0.2618 -0.35 0.28 -0.00 0.17 -0.81 0.32 0.35 Group 0.26 -0.42 0.05 0.20 5.73 -2.08 0.0000 0.0379 Rate -0.02 Shared Reflection Recall your hypotheses about the impact of the independent variables on the number of daily check-ins. Are there any coefficients that surprise you or contradict your original hypotheses? Develop a possible explanation for why the estimated coefficients might make sense in the context of the problem Do the coefficients for payday or any of the holidays surprise you? What was your original hypothesis for those variables? Interpret the coefficients and explain why they support or contradict your intuition. Do any of the coefficients for day of the week surprise you? What was your original hypothesis for those variables? Interpret the coefficients and explain why they support or contradict your intuition. Do any of the coefficients for the number of rooms reserved on a given day to a particular type of guest (TotalRewards, Special Event, VIP, FreeIndependent, Wholesale, Group) surprise you? What was your original hypothesis for those variables? Interpret the coefficients and explain why they support or contradict your intuition. Does the coefficient Rate surprise you? What was your original hypothesis for that variable? Interpret the coefficient and explain why it supports or contradicts your intuition. MINIMUM MAXIMUM Words 1000 50 Enter your reflection