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By Michael J. Fry

This ebook presents assurance over the entire variety of analytics--descriptive, predictive, prescriptive--not coated by way of the other unmarried booklet. It comprises step by step directions to aid scholars the best way to use Excel and strong yet effortless to take advantage of Excel accessories equivalent to XL Miner for info mining and Analytic Solver Platform for optimization and simulation.

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Three 2. 7 three. 7 four. 7 four. 7 20. 2 x five eighty four. 6 y five 26. three sxy five ( xi 2 x ) ( y i 2 y ) g ( xi 2 x ) ( y i 2 y ) 166. forty two five five 12. eight n21 14 2 1 21. seventy eight 24. 08 10. fifty eight 19. seventy eight five. ninety eight zero. forty eight zero. 28 21. eighty two four. 08 20. seventy two nine. 18 12. fifty eight 25. 38 34. seventy eight 166. forty two © Cengage studying 2015 desk 2. 15 Copyright 2013 Cengage studying. All Rights Reserved. will not be copied, scanned, or duplicated, in entire or partially. as a result of digital rights, a few 3rd social gathering content material will be suppressed from the publication and/or eChapter(s). Editorial overview has deemed that any suppressed content material doesn't materially impact the final studying adventure. Cengage studying reserves the appropriate to take away extra content material at any time if next rights regulations require it. 2. eight dossier BottledWater If info include a inhabitants of n observations, the inhabitants covariance sxy is computed through: g ( xi 2 μx ) g ( yi 2 μy ) . σxy five n observe that this equation is identical to equation (2. 8), yet makes use of inhabitants parameters rather than pattern estimates (and divides via n rather than n – 1 for technical purposes past the scope of this book). determine 2. 24 The covariance calculated in desk 2. 15 is sxy five 12. eight. as the covariance is larger than zero, it shows a good dating among the hot temperature and revenues of bottled water. This verifies the connection we observed within the scatter chart in determine 2. 23 that because the hot temperature for an afternoon raises, revenues of bottled water as a rule raise. If the covariance is close to zero, then the x and y variables should not linearly similar. If the covariance is under zero, then the x and y variables are negatively comparable, because of this as x raises, y ordinarily decreases. The pattern covariance is also calculated in Excel utilizing the COVARIANCE. S functionality. determine 2. 24 exhibits the information from desk 2. 14 entered into an Excel Worksheet. The covariance is calculated in mobile B17 utilizing the formulation 5COVARIANCE. S(A2:A15, B2:B15). The A2:A15 defines the variety for the x variable (high temperature), and B2:B15 defines the diversity for the y variable (sales of bottled water). determine 2. 25 demonstrates numerous attainable scatter charts and their linked covariance values. One challenge with utilizing covariance is that the importance of the covariance price is tough to interpret. greater sxy values don't inevitably suggest a higher linear dating as the devices of covariance rely on the devices of x and y. for instance, think we're CALCULATING COVARIANCE AND CORRELATION COEFFICIENT FOR BOTTLED WATER revenues utilizing EXCEL A 1 2 three four five 6 7 eight nine 10 eleven 12 thirteen 14 15 sixteen 17 18 extreme temperature (degrees F) seventy eight seventy nine eighty eighty eighty two eighty three eighty five 86 87 87 88 88 ninety ninety two B Bottled Water revenues (cases) 23 22 24 22 24 26 27 25 28 26 29 30 31 31 A B hot temperature Bottled Water (degrees F) revenues (cases) 1 23 seventy eight 2 22 seventy nine three 24 eighty four 22 eighty five Covariance: 5COVARIANCE. S(A2:A15,B2:B15) 24 eighty two 6 Correlation Coefficient: 5CORREL(A2:A15,B2:B15) 26 eighty three 7 27 eighty five eight 25 86 nine 28 87 10 26 87 eleven 29 88 12 30 88 thirteen 31 ninety 14 31 ninety two 15 sixteen 12. eighty Covariance: 17 zero.

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