Many continuous variables used in business closely follow a normal distribution. To determine whether a set of data can be approximated by the normal distribution, replica jaeger lecoultre master you either compare the characteristics of the data with the theoretical properties of the normal distribution or construct a normal probability plot. The normal distribution has several important theoretical properties: It is symmetrical; knockoff maurice lacroix thus, the mean and median are equal. It is bell-shaped; thus, the empirical rule applies. The interquartile range equals 1.33 standard deviations. The range is approximately equal to 6 standard deviations. Many continuous variables have characteristics that approximate these theoretical properties. However, other continuous variables are often neither normally distributed nor approximately normally distributed. For such variables, the descriptive characteristics of the data are inconsistent with the properties of a normal alain silberstein watches for sale distribution. One approach that you can use to determine whether a variable follows a normal distribution is to compare the observed characteristics of the variable with what would be expected if the variable followed a normal distribution. To do so, you can Construct charts and observe their appearance. For small- or moderate-sized data sets, create a stem-and-leaf display or a box plot. For large data sets, in addition, plot a histogram or polygon. Compute descriptive statistics and compare these statistics with the theoretical properties of the normal distribution. Compare the mean and median. Is the interquartile range approximately 1.33 times the standard deviation? Is the range approximately 6 times the standard deviation? Evaluate how the replica cartier tonneau values are distributed. buy baume mercier Determine whether approximately two-thirds of the values lie between the mean and ��1 standard deviation. Determine whether approximately four-fifths of the values lie between the mean and ��1.28 standard deviations. Determine whether approximately 19 out of every 20 values lie between the mean and ��2 standard deviations. Constructing the Normal Probability Plot A normal probability plot is a visual display that helps you evaluate whether the data are normally distributed. One common plot is called the quantile�Cquantile plot. To create this plot, knockoff patek philippe you first transform each ordered value to a Z value. If the data are normally distributed, the points will plot along an approximately straight line. If the data are right-skewed, the data will rise more slowly at first and then rise at a faster rate for higher values of the variable being plotted as is the case with the quantile vacheron constantin replica plot, if the data are patek philippe clones normally distributed, the points will plot along an approximately straight line. However, if the data are right-skewed, the curve will rise more rapidly at first and then level off. If the data are left-skewed, the data will rise more slowly at first and then rise at a faster ferrari watches for sale rate for higher values of the variable being plotted. Observe that the values rise more rapidly at first and then level off, indicating a right-skewed distribution. Statistics Homework Help