how to interpret histogram with normal curve in spss

Skewed right. A z-score is a standard score obtained by subtracting the mean from a score and dividing by the standard deviation In SPSS, Compute a new variable Or, choose Descriptives and "save standardized values as variables". Use histograms to understand the center of the data. In this standardizing values does not normalize them in any way. ways of calculating these values, so SPSS clarifies what it is doing by i N ( 0, 2) which says that the residuals are normally distributed with a mean centered around zero. Also, since there are 3 students with a shoe size between 6 and 7, and there are 10 students with a shoe size between 7 and 8, we have that there are 13 students total (10 + 3 = 13) with a shoe size that is less than a size 8. Drive Student Mastery. The result of doing so is that \(z\) is given a standard of = 0 and = 1. The following two examples will use these steps and definitions to demonstrate how to interpret a histogram. For skewness, if the value is greater than + 1.0, the distribution is right skewed. Skewness indicates that the data may not be normally distributed. A histogram is described as uniform if every value in a dataset occurs roughly the same number of times. Sometimes, the median is i. Kurtosis Kurtosis is a measure of tail extremity reflecting either the presence of outliers in a distribution or a distributions propensity for producing outliers (Westfall,2014). A skewed right histogram looks like a lopsided mound, with a tail going off to the right:

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