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Above the fold is an old newspaper journalism term that has been reappropriated in the Web design world Think of the way that the most important headlines and photos are laid out on the newspaper front page to fit above the horizontal crease This allows the viewer to see as much essential information and images as possible in a single view In Web design, above the fold refers to the amount of the Web page the user views on the screen without having to scroll down For eBay listings, keeping important information above the fold is particularly important You want your potential customers to get as much information as possible within a single view of the screen When you go into any eBay item listing page, the view you ll immediately see above the fold is eBay s own information with the title, item number, seller information, and bidding information Figure 3-3 depicts the standard view of the screen that appears when users open any eBay listing page Unfortunately, the part of the listing that you have power to control (the description and more images) never appears above the fold However, you should design your listing layout so that once the viewer has scrolled once, she will be able to view your item description and its images in one screen without having to scroll much more Just as newspaper readers are less likely to continue reading a story that goes below the fold, the same holds true for scrolling and eBay customers Remember that it s as easy for a potential customer to click off your site as it is for him to scroll all over your page You want to keep his attention on your item until he has become engaged in what you re selling You need to do everything in your power to keep his hand off that mouse until he s ready to click the bid button.

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Figure 3-3 Above the fold view of typical eBay listing Note that this is standard eBay information; the viewer must scroll down to see the seller s item description and images

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In the first two sections of this chapter, we used confidence intervals to make estimates about population values In one of the examples, we went further and stated that because 0 was not in the confidence interval, 0 was not a likely population value from which to have drawn the sample that generated the interval Now, of course, 0 could be the true population value and our interval just happened to miss it As we progress through techniques of inference (making predictions about a population from data), we often are interested in sample values that do not seem likely A finding or an observation is said to be statistically significant if it is unlikely to have occurred by chance That is, if we expect to get a certain sample result and don t, it could be because of sampling variability (in repeated sampling from the same population, we will get different sample results even though the population value is fixed), or it could be because the sample came from a different population than we thought If the result is far enough from expected that we think something other than chance is operating, then the result is statistically significant

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