![]() ![]() Previously, you saw how a measure of central tendency indicates where most observations fall. ![]() Measures of Dispersion (Standard Deviation, Variance, Range) Half the data points fall above 44.9kg, and half fall below.įor more information about the different measures of central tendency, their calculations, how data types and distribution properties affect them, graphical representations, and when to use each type, read my post about Measures of Central Tendency. When the mean is greater than the median, it indicates that the distribution is right-skewed. However, there is a difference between the weight mean (46.3kg) and median (44.9kg). The mean tells us that the height distribution centers on 1.51m. That’s a good sign that the heights follow a symmetric distribution, making the mean a good choice. For symmetric distributions, the mean and median will be very close together. What can we learn by comparing the mean and median for both variables? For the height data, they are virtually equal, 1.51m and 1.50m, respectively. Related post: Data Types and How to Graph Them Central Tendency for our Descriptive Statistics Example However, the mode really is not a good measure for these data. That process produced clumps of rounded values. The study’s nurse collected the underlying data in inches and pounds, rounded them to the nearest unit, and converted them to their metric equivalents. Thanks to a data collection artifact, my data are continuous, but Excel displays the mode anyway. That happens because continuous data are unlikely to have exactly duplicated values, a requirement for the mode. Excel frequently displays “N/A” for the mode when you have continuous data. The example data are continuous variables. It’s best for categorical and ordinal data. Mode: This measure represents the value that occurs most frequently in your data.Half the values fall above the median while half are below it. Median: This value splits your data in half.It’s best for data that follow symmetric distributions. It’s the sum of all observations divided by the number of observations. Mean: This measure is the one with which you’re most familiar.Excel presents three measures of central tendency. It’s the center of the distribution of values. If you want to learn more about the statistics, be sure to click the links for more detailed information! Central Tendencies (Mean, Median, Mode)Ī measure of central tendency describes where most of the values in the dataset occur. Consequently, the following discussion doesn’t strictly follow the order of the output. However, I’ll group the results into categories that make sense. Generally, we’ll work our way down from the top of Excel’s descriptive statistics output. Etc.įor our example dataset, fill in the dialog box as shown below. If you enter 2, it shows the 2 nd highest and lowest values. If you enter 1, Excel displays the highest and lowest values. Check Kth Largest and Kth Smallest to display a high and low value.For more information about confidence levels, read my post about confidence intervals. Check the Confidence Level for Mean box to display a confidence interval for the mean.Check the Summary statistics box to display most of the descriptive statistics (central tendency, dispersion, distribution properties, sum, and count).In Output options, choose where you want Excel to display the results.This option makes the output easier to interpret. Check the Labels in first row checkbox if you have meaningful variable names in row 1.Alternatively, you can include one variable per row. I always include one variable per column as this format is standard across software. In Grouped By, choose how your variables are organized.While you can explore more than one variable, the analysis assesses each variable in a univariate manner (i.e., no correlation). You can include multiple variables as long as they form a contiguous block. Under Input Range, select the range for the variables that you want to analyze.Step-by-Step Instructions for Filling in Excel’s Descriptive Statistics Box ![]()
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