Do problem XXXXXXXXXXSubmit one Excel file with your models and responses.62. The fileDownload P12_62.xlsxcontains data on a motel chain’s revenue and advertising.Use these data and multiple...

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Do problem 12.62. Submit one Excel file with your models and responses.


62. The file


Download P12_62.xlsx


contains data on a motel chain’s revenue and advertising.



  • Use these data and multiple regression to make predictions of the motel chain’s revenues during the next four quarters. Assume that advertising during each of the next four quarters is $50,000. (Hint: Try using advertising, lagged by one quarter, as an explanatory variable.)

  • Use simple exponential smoothing to make predictions for the motel chain’s revenues during the next four quarters.

  • Use Holt’s method to make forecasts for the motel chain’s revenues during the next four quarters.

  • Use Winters’ method to determine predictions for the motel chain’s revenues during the next four quarters.

  • Which of these forecasting methods would you expect to be the most accurate for these data?

  • PLEASE SUBMIT THE ANSWER IN EXCEL FILE




Data QuarterAdvertisingRevenue 1$30,000$1,200,000 2$20,000$880,000 3$15,000$1,800,000 4$40,000$1,050,000 5$10,000$1,700,000 6$50,000$350,000 7$5,000$2,500,000 8$40,000$760,000 9$20,000$2,300,000 10$10,000$1,000,000 11$60,000$1,570,000 12$5,000$2,430,000 13$35,000$1,320,000 14$15,000$1,400,000 15$70,000$1,890,000 16$25,000$3,200,000 17$30,000$2,200,000 18$60,000$1,440,000 19$80,000$4,000,000 20$50,000$4,100,000 This is fictitious data.
hw-9-wechf4ko.xlsx
Answered Same DayNov 16, 2022

Answer To: Do problem XXXXXXXXXXSubmit one Excel file with your models and responses.62. The fileDownload...

Rochak answered on Nov 17 2022
39 Votes
Data
    Quarter    Advertising    Revenue
    1    $30,000    $1,200,000
    2    $20,000    $880,000
    3    $15,000    $1,800,000
    4    $40,000    $1,050,000
    5    $10,000    $1,700,000
    6    $50,000    $350,000
    7    $5,000    $2,500,000
    8    $40,000    $760,000
    9    $20,000    $2,300,000
    10    $10,000    $1,000,000
    11    $60,000    $1,570,000
    12    $5,000    $2,430,000
    13    $35,000    $1,320,000
    14    $15,000    $1,400,000
    15    $70,000    $1,890,000
    16    $25,000    $3,200,000
    17    $30,000    $2,200,000
    18    $60,000    $1,440,000
    19    $80,000    $4,000,000
    20    $50,000    $4,100,000
This is fictitious data.
Regression
    SUMMARY OUTPUT
    Regression Statistics
    Multiple R    0.1756619542
    R Square    0.0308571221
    Adjusted R Square    -0.0261512824
    Standard Error    1042407.40411312
    Observations    19
    ANOVA
        df    SS    MS    F    Significance F
    Regression    1    588154612820.926    588154612820.926    0.5412732101    0.4719352788
    Residual    17    18472424334547.5    1086613196149.85
    Total    18    19060578947368.4
        Coefficients    Standard Error    t Stat    P-value    Lower 95%    Upper 95%    Lower 95.0%    Upper 95.0%        Forecast
    Intercept    1622390.02521715    434119.743762019    3.7371947453    0.0016398933    706477.427183033    2538302.62325126    706477.427183033    2538302.62325126        Quarter    Advertising    Revenue    Forecast        Absolute Percent Error
    Advertising    7.9134211264    10.756129239    0.7357127225    0.4719352788    -14.7800278992    30.6068701519    -14.7800278992    30.6068701519        1    $30,000    $1,200,000    $ 11,118,495
                                            2    $20,000    $880,000    $ 8,586,201        875.70
                                            3    $15,000    $1,800,000    $ 15,866,548        781.47
                                            4    $40,000    $1,050,000    $ 9,931,482        845.86
    RESIDUAL OUTPUT                                        5    $10,000    $1,700,000    $ 15,075,206        786.78
                                            6    $50,000    $350,000    $ 4,392,087        1,154.88
    Observation    Predicted Y    Residuals                                7    $5,000    $2,500,000    $ 21,405,943        756.24
    1    1780658.44774447    -900658.447744466                                8    $40,000    $760,000    $ 7,636,590        904.81
    2    1741091.34211264    58908.6578873633                                9    $20,000    $2,300,000    $ 19,823,259        761.88
    3    1938926.87027178    -888926.870271785                                10    $10,000    $1,000,000    $ 9,535,811        853.58
    4    1701524.23648081    -1524.236480807                                11    $60,000    $1,570,000    $ 14,046,461        794.68
    5    2018061.08153544    -1668061.08153544                                12    $5,000    $2,430,000    $ 20,852,003        758.11
    6    1661957.13084898    838042.869151023                                13    $35,000    $1,320,000    $ 12,068,106        814.25
    7    1938926.87027178    -1178926.87027178                                14    $15,000    $1,400,000    $ 12,701,180        807.23
    8    1780658.44774447    519341.552255534                                15    $70,000    $1,890,000    $ 16,578,756        777.18
    9    1701524.23648081    -701524.236480807                                16    $25,000    $3,200,000    $ ...
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