Why Are There Extreme Values in Data? Several reasons account for outliers in datasets, with the simplest being the natural variance in human populations. Humans differ in many ways, and a certain degree of variation is normal. Whether something is considered an outlier often depends on the sample being studied. For instance, a person over …
Descriptive analysis is a vital part of statistics, serving to summarize and describe data. With descriptive statistics, we can identify characteristic features of a sample or a population and infer conclusions about the underlying distribution. In this article, we will focus on descriptive analysis in SPSS, learning how to calculate and interpret various descriptive statistics …
The Spearman correlation, also called rank correlation, is a statistical method for measuring the strength and direction of a monotonic relationship between two variables. Unlike the Pearson correlation, which measures the linear relationship between variables, the Spearman correlation examines the monotonic relationship, which can also be described as non-linear. It is often used in social …
What is the normal distribution? The normal distribution, also known as the Gaussian normal distribution or bell curve, is an important distribution in statistics and occurs in many different applications. It describes a symmetrical distribution in which the data are distributed around a mean value (the arithmetic mean). The normal distribution has a characteristic course …
Understanding Reliability Analysis Reliability analysis provides insights into the dependability of an analysis. It measures the extent to which a method consistently yields the same results upon repeated applications. If you were to repeat your experiment, would you obtain similar outcomes? A “No” answer implies a problem. Perfect reliability means a measurement (be it an …
Linearity in statistics An important requirement for performing calculations in SPSS is linearity between the dependent variable and the independent variables. Linearity states that the relationship between the variables is linear, meaning that the change in the dependent variable is proportional to the change in the independent variable. If linearity is not present, the results …