Explore Flipsnack. Transform boring PDFs into engaging digital flipbooks. Share, engage, and track performance in the same platform.
From magazines to catalogs or private internal documents, you can make any page-flip publication look stunning with Flipsnack.
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Pre-made templates to create stunning publications in minutes
Here are eight reasons why you should consider choosing interactive, digital flipbooks instead of boring and static PDFs. Check them out!
polygons are used to represent continuous data. In this manner, the video explains the different basic graph types available to us for statistical analysis. The second video also has an appropriate title because it explains the relationship between histograms and stem-and-leaf plots. Stem-and-leaf plots can be converted into histograms by turning the stem-and-leaf plot 90 degrees so that the leaves are where the bars are. The number of leaves on each stem then corresponds to the frequency, and the stem corresponds to the x-axis bins. The video then gives several examples of the conversion of stem and leaf plots into histograms. The third video is aptly named because it provides an in-depth explanation of stem-and- leaf plots. The video tells viewers how to draw a stem-and-leaf plot and also explains its functions: a stem-and-leaf plot is used to plot small amounts of quantitative data. The last video’s title is also fit for its con tent. The video explained thoroughly the measures of a center, the mean, the median, the mode, and then trimmed mean. The video also explained how to find each measure of center as well as its use. The mean is the least resistant of the four measure of centers, while the median is the most resistant, and the trimmed mean is in between the two. The video title was very concise and described the content of the video effectively. List any formulas introduced and explain what each variable represents and how the formula is used. (If no formulas were introduced say NONE!) ∑ The equation shown above is used to calculate the arithmetic mean of a data distribution, where x is the arithmetic mean, n is the total number of data values, and x1, x2, x3 and xn are the data values. Xi simply denotes the summation of all data values from i=1 to a number n.
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