![]() Line charts can show continuous data over time on an evenly scaled axis, so they're ideal for showing trends in data at equal intervals, like months, quarters, or fiscal years. In a line chart, category data is distributed evenly along the horizontal axis, and all value data is distributed evenly along the vertical axis. Use this chart when you want to compare data across both categories and data series.ĭata that's arranged in columns or rows on a worksheet can be plotted in a line chart. Use this chart when you have two or more data series and you want to emphasize the contributions to the whole, especially if the total is the same for each category.ģ-D column 3-D column charts use three axes that you can change (a horizontal axis, a vertical axis, and a depth axis), and they compare data points along the horizontal and the depth axes. A 3-D 100% stacked column chart shows the columns in 3-D format, but it doesn’t use a depth axis. Use this chart when you have multiple data series and you want to emphasize the total.ġ00% stacked column and 3-D 100% stacked column A 100% stacked column chart shows values in 2-D columns that are stacked to represent 100%. A 3-D stacked column chart shows the stacked columns in 3-D format, but it doesn’t use a depth axis. Stacked column and 3-D stacked column A stacked column chart shows values in 2-D stacked columns. Names that are not in any specific order (for example, item names, geographic names, or the names of people). Specific scale arrangements (for example, a Likert scale with entries like Strongly agree, Agree, Neutral, Disagree, Strongly disagree). Ranges of values (for example, item counts). Use this chart when you have categories that represent: A 3-D clustered column chart shows columns in 3-D format, but it doesn’t use a third value axis (depth axis). A column chart typically displays categories along the horizontal (category) axis and values along the vertical (value) axis, as shown in this chart:Ĭlustered column and 3-D clustered columnĪ clustered column chart shows values in 2-D columns. ![]() Different measures of central tendency and variability, as well as different degrees of skewness, can produce a wide range of distribution shapes.Data that’s arranged in columns or rows on a worksheet can be plotted in a column chart. ![]() In summary, the shape of a distribution is determined by the combination of its central tendency, variability, and skewness. As it has essential importance because it could affect the statistical methods you are going to employ later. Whenever working with any data don’t forget to observe shape of a distribution.
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