![]() ![]() ![]() Since our products are watches, it makes sense that they weigh less one kilogram. Move to Product Weight (kg), and in cell D2 enter =rand(). You now have random prices for your products. Use the autofill cross in the bottom right to fill out the following rows. In cell C2, type =rand()*50 and press enter. Let’s use it for Product Price and Product Weight. The rand() function output is a number between 0 and 1, which means you can multiply it by a constant to get a percent of that constant.Put this into cell B2, then slide the autofill cross in the bottom right of that cell down to cell B11 to match the number of Product ID (pro tip: you can double click it to automatically match the number of cells in an adjacent column). Imagine we only have 3 product categories. In our case, let’s use it for Product Category. The randombetween() function output is a random number between two parameters that you provide.Use rand() and randombetween() Excel formulas to fill in numeric dimensions with dummy data.Excel will automatically create a sequence of ten PNs. To do this, choose cell A1 in an Excel sheet and write “Product ID.” In cell A2, write “PN1.” In cell A3, write “PN2.” Then highlight those two cells and drag the arrow in the bottom right corner down 8 cells. Once you know them, fill in the observation IDs. For example, you might use “Product Category, Product Price, Product Weight, Product Brand” as dimensions. You need to identify what information you will include about each product, and include them as headers in your data table. They’re a piece of information about the observation ID. Dimension (or field) is another word for characteristic or trait. For example, you might use “PN1, PN2, PN3… PN10” as observation IDs for products. You need to identify the observations on which the table will be based. In the case of products, observation IDs could be product names or a numeric substitute. ![]() Observation IDs are unique identifiers for each line of the data table. Identify observation IDs for the data set. ![]()
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