Question

In: Statistics and Probability

Daily Gross Revenue=766.981 + 2.977 * Daily Tour Income – 12.31 * Number of Tourists Report...

Daily Gross Revenue=766.981 + 2.977 * Daily Tour Income – 12.31 * Number of Tourists

  1. Report and interpret of both coefficients of determination.

  2. Report and explain the significance of each independent variable in both regressions.

  3. Report and explain the significance of both models.

  4. Predict y for a fictitious set of x values for both models.

  5. Years Weekend Daily Tour Income Number of Tourists=y Daily Gross Revenue Total Daily Income
    1 Friday 3378 432 4838.95 8216.95
    1 Saturday 1198 139 3487.78 4685.78
    1 Sunday 3630 467 4371.3 8001.3
    2 Friday 4550 546 6486.48 11036.48
    2 Saturday 2467 198 3437.39 5904.39
    2 Sunday 3593 452 4571.43 8164.43
    3 Friday 898 119 2515.15 3413.15
    3 Saturday 2812 342 5462.11 8274.11
    3 Saturday 2650 321 5498.89 8148.89
    4 Friday 3230 402 5071.14 8301.14
    4 Saturday 4798 523 8051.43 12849.43
    4 Sunday 3253 353 4291.95 7544.95
    5 Friday 2848 347 4545 7393
    5 Saturday 4632 534 8865.01 13497.01
    5 Sunday 3767 412 4710.64 8477.64
    6 Friday 4499 529 10752.74 15251.74
    6 Saturday 3868 422 6435.63 10303.63
    6 Sunday 2489 288 3389.37 5878.37
    7 Friday 3448 367 6129.58 9577.58
    7 Saturday 3612 406 7357.12 10969.12
    7 Sunday 1937 216 2121.76 4058.76
    8 Friday 2548 294 4738.86 7286.86
    8 Saturday 2833 317 4141.98 6974.98
    8 Sunday 2214 284 4878.35 7092.35
    9 Friday 1520 169 4102.49 5622.49
    9 Saturday 4322 462 8639.55 12961.55
    9 Sunday 1833 203 3946.71 5779.71
    10 Friday 2271.63 235 4236.31 6507.94
    10 Saturday 2407.88 266 5613.27 8021.15
    10 Sunday 1772.17 182 5580.17 7352.34
    11 Friday 1494 177 3833.52 5327.52
    11 Saturday 1998 213 3986.57 5984.57
    11 Sunday 1388 165 2721.56 4109.56
    12 Friday 1925 190 3952.19 5877.19
    12 Saturday 2695 243 6281.3 8976.3
    12 Sunday 1525 172 3356.14 4881.14
    13 Friday 1725 187 3822.59 5547.59
    13 Saturday 2450 253 4141.75 6591.75
    13 Sunday 1407.5 173 3312.41 4719.91
    14 Friday 2394 242 4571.5 6965.5
    14 Saturday 3012 311 6363.3 9375.3
    14 Sunday 2058 239 3502.22 5560.22
    15 Friday 2427 267 5881.13 8308.13
    15 Saturday 3189 336 10409.13 13598.13
    15 Sunday 2109 178 4955.05 7064.05
    16 Friday 2244 184 4347.41 6591.41
    16 Saturday 3195 274 4935.17 8130.17
    16 Sunday 1017 114 3486.27 4503.27
    17 Friday 3470 325 6290.99 9760.99
    17 Saturday 5323 478 13132.55 18455.55
    17 Sunday 2345 242 5014.45 7359.45
    18 Friday 1671 177 2740.23 4411.23
    18 Saturday 2321.94 246 4423.31 6745.25
    18 Sunday 1542 182 2650.48 4192.48

Solutions

Expert Solution

  • Analysis
    regression 1:

    1)  
    regression equation:   
    Daily Gross Revenue = 1408.52 + 12.68*number of tourists  
      
    2)  
    R^2 =    48.91%
      
    3)  
    Ho: beta1 is not significant  
    h1: beta1 is significant  
    With t=7.05, p<5%, I reject ho and conclude that beta1 is significant.  
      
    4)  
    Ho: model is not significant  
    h1: model is significant  
    With F=49.79, p<5%, I reject ho and conclude that the model is significant.

    5)
    when x= 119,
    predicted Y = 1408.52 + 12.68*119 = 2917.44

    regression 2:

    1)  
    regression equation:   
    Daily Gross Revenue = 748.65179 + 1.6362*Daily Tour Income  
      
    2)  
    R^2 = 62.707%
      
    3)  
    Ho: beta1 is not significant  
    h1: beta1 is significant  
    With t=9.35, p<5%, I reject ho and conclude that beta1 is significant.  
      
    4)  
    Ho: model is not significant  
    h1: model is significant  
    With F=87.43, p<5%, I reject ho and conclude that the model is significant.

    5)
    when x= 3012,
    predicted Y = 748.65179 + 1.6362*3012 = 5676.88619

    procedure
    data -> data analysis -> regression

    regression 1: dependent variable: Daily Gross Revenue
    independent variable: Number of Tourists

    regression 2: dependent variable: Daily Gross Revenue
    independent variable: Daily Tour Income

    output
    regression 1:

    SUMMARY OUTPUT
    Regression Statistics
    Multiple R 0.699382402
    R Square 0.489135744
    Adjusted R Square 0.479311431
    Standard Error 1543.231194
    Observations 54
    ANOVA
    df SS MS F Significance F
    Regression 1 118573929.8 1.19E+08 49.78829188 4.02752E-09
    Residual 52 123841250.9 2381563
    Total 53 242415180.7
    Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
    Intercept 1408.526138 566.125925 2.488009 0.016088648 272.5113593 2544.541 272.5114 2544.541
    Number of Tourists 12.68245322 1.797378968 7.056082 4.02752E-09 9.075748453 16.28916 9.075748 16.28916

    regression 2:

    SUMMARY OUTPUT
    Regression Statistics
    Multiple R 0.791878228
    R Square 0.627071127
    Adjusted R Square 0.619899418
    Standard Error 1318.533714
    Observations 54
    ANOVA
    df SS MS F Significance F
    Regression 1 152011560.6 1.52E+08 87.43677682 1.00186E-12
    Residual 52 90403620.06 1738531
    Total 53 242415180.7
    Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
    Intercept 748.6517999 500.552028 1.495652 0.140789091 -255.7793278 1753.083 -255.779 1753.083
    Daily Tour Income 1.636240094 0.174984653 9.350763 1.00186E-12 1.285107699 1.987372 1.285108 1.987372

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