Central Tendency and Variability
This paper will perform an analysis using the Real Estate data found in Appendix J from the course material. It will include measures of central tendency and measures of variability. The variables selected are home selling price and home square footage. For both of the selected variables, calculations will be completed on the mean, mode, median, interquartile range and standard deviation.
Central tendency is the measure of location using a value to describe the center of a set of data (Lind, Marchal, & Wathen, 2003, p. 56). This measure of location is often referred to as the average and used to identify the center value (Lind et al., p. 56). However, when calculating the average, or the most commonly used arithmetic mean, the data may be unduly influenced by a few high or low values. Relying erroneous data representations can lead to erroneous conclusions (Lind et al., p. 56). The dispersion, often called the variation or spread, should be considered to compare data (Lind et al., p. 56). To evaluate the dispersion, calculate the range, mean deviation, variance and the standard deviation (Lind et al., p. 56). The importance of studying the dispersion is to show how closely clustered the data is around the mean, which will indicate the mean reliability (Lind et al., p. 71). Creating a visual diagram of the central location will show a normal distribution, positively skewed distribution or a negatively skewed distribution. A normal distribution reveals the data is evenly dispersed. However a positively or negatively skewed distribution reveals data influenced by extremely high and low numbers, respectively.
The mean can be expressed, in a population by the population mean which is derived from the sum of all the values in the ...