Significant Variation in Product Distribution by Quantity Ordered
Percentage Makeup of Products Across Different Quantities Ordered
___1 ___2 ___3 ___4 ___5 ___6 ___7 ___8 ___9 ___10 ___11 ___12 ___13 ___14 ___15 ___16 ___17 ___18 ___19 ___20
0 #dccfe5 Monitor #bea3d7 Tablet #ffc1c0 Desk #e77c7d Keyboard #c1ebb8 Headphones #6fd76f External Hard Drive #ffd6ae Laptop #ffb26e Chair #ceddf1 Mouse #65b0e4 Printer
Key takeaway: The data suggests that certain products are more likely to be ordered in specific quantities, which could inform inventory and marketing strategies. The data shows that the quantity ordered has a noticeable effect on the distribution of products. For instance, the percentage of Monitor orders is significantly higher for Quantity Ordered 1 (57.1%), Quantity Ordered 6 (42.9%), and Quantity Ordered 7 (33.3%) compared to its overall average of 12%. Similarly, Desk orders are substantially higher for Quantity Ordered 8 (40.0%) and moderately higher for Quantity Ordered 10 (30.0%) compared to its average of 10%. External Hard Drive orders are moderately higher for Quantity Ordered 6 (28.6%) compared to its average of 10%. Chair orders are moderately higher for Quantity Ordered 9 (25.0%) compared to its average of 8%. Tablet orders are notably lower for Quantity Ordered 6 (0%) compared to its average of 16%. Mouse orders are moderately higher for Quantity Ordered 8 (20.0%) and Quantity Ordered 6 (14.3%) compared to its average of 5%. Printer orders are moderately higher for Quantity Ordered 4 (20.0%) and Quantity Ordered 9 (16.7%) compared to its average of 6%. Laptop orders are moderately higher for Quantity Ordered 3 (22.2%) compared to its average of 10%. The statistical test results indicate that the differences in the distribution of products by quantity ordered are significant for Monitors (p-value = 0.00), suggesting that the observed variations are not due to random chance. For other products, the p-values are higher, indicating that the differences are not statistically significant. In summary, the data reveals specific trends in product orders by quantity, which can be useful for optimizing stock levels and targeting marketing efforts.