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One of the most popular and effective multidimensional statistical approaches is regression analysis. It postulates the nature and extent of significant relationships between the variables in a data set. Once you understand how to apply regression, you can identify and determine the relationship between two or more variables. Regression methods help researchers make inferences and forecast future outcomes and behaviours. For example, sales forecasts and weather forecasts depend upon the regression analysis. However, there are some common mistakes that every statistician mistakes in regression methods. These mistakes compromise the validity of the results and lead to incorrect inferences and predictions. This article will tell you about the eight mistakes that every statistician makes in regression analysis.

The first and most important step in dissertation research is selecting the right research method. In this way, you identify the research question and the purpose of your study. When you identify, the next step is to consider which method is appropriate for your dissertation research work. There are 3 methods for your dissertation research: quantitative, qualitative, and mixed-method. The most effective of all of these is the mixed method approach. Through this method, you can use both kinds of data that are: quantitative and qualitative, in your research work.

Exploratory data analysis is very commonly used among data scientist and researchers. It is because it can allow you to get deep insights from a particular dataset. In this way, a data scientist can draw a particular outcome from a dataset with the help of the EDA process. However, it is a very difficult process. Thus, you need to know an effective method before doing this analysis. This article will give you the best method to do an exploratory data analysis.