Đang chuẩn bị liên kết để tải về tài liệu:
Microsoft Excel 2010: Data Analysis and Business Modeling phần 8

Sau khi nhấp OK, bảng tính mới trông giống như một hiển thị trong hình 47-6. Bạn có thể nhìn thấy, ví dụ, 1.317 đơn vị sản phẩm đã được bán ra trong tháng hai, 597 đơn vị F Sản phẩm đã được bán vào tháng Giêng, và vv.đã hoàn thành Củng cố hộp thoại | 484 Microsoft Excel 2010 Data Analysis and Business Modeling In the Two Way ANOVA with Interaction worksheet I changed the data from the previous example to the data shown in Figure 57-10. After running the analysis for a two-factor ANOVA with replication I obtained the results shown in Figure 57-11. c _L 0 E F G 2 3 Price 4 Low Medium High 5 Low 41 21 15 6 Adv 25 20 14 7 23 16 13 8 Medium 28 28 14 9 30 22 13 10 32 18 12 11 High 50 34 13 12 51 40 13 13 52 32 13 FIGURE 57-10 Sales data with interaction between price and advertising. c D E F G H I 43 AN OVA 44 Source of Variation ss df MS F P-vafue F crit 45 Sample 828.963 2 414.48 24.22 7.86E-06 3.55456 46 Columns 2498.74 2 1249.4 73.02 2.31E-09 3.55456 47 Interaction 509.926 4 127.48 7.45 0.001006 2.92775 48 Within 308 18 17.111 49 50 Total 4145.63 26 51 Std dev 4.137 FIGURE 57-11 Output for the two-factor ANOVA with interaction. In this data set the p-value for interaction is .001. When you see a low p-value less than .15 for interaction you do not even check p-values for row and column factors. You simply forecast sales for any price and advertising combination to equal the mean of the three observations involving that price and advertising combination. For example the best forecast for sales during a month with high advertising and medium price is 34 40 32 _ 106 _ 3 - . ---- ---- 35.555 units 43 The standard deviation of forecast errors is again the square root of the mean square within h 17.11 4.14 Thus you can be 95 percent sure that the sales forecast is accurate within 8.26 units. Chapter 57 Randomized Blocks and Two-Way ANOVA 485 Figure 57-12 illustrates why this data exhibits a significant interaction between price and advertising. For a low and medium price increased advertising increases sales but if price is high increased advertising has no effect on sales. This explains why you cannot use equation 2 to forecast sales when a significant interaction is present. After all how can you talk about an .