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The idea behind a research essay is for the writer to propose a new discovery and trying to persuade the reader that it is a valid discovery.

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When adding an API to your web service, you have to choose how to encode the data you send across the line. XML is one common choice for this, but it can grow arcane and cumbersome pretty quickly. Lots of webservice authors want to avoid thinking about XML, and instead choose formats that provide a few simple data types that correspond to common data structures in modern programming languages. In other words, JSON and YAML.

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In any research, selecting a sample is crucial for drawing a valid conclusion. If you want a sample evenly distributed throughout the whole population selected for your study, then the systematic sampling method is the best choice. Choosing samples systematically after a specified interval is better than choosing samples randomly because it can help you get quality data and avoid biased samples. You can save a lot of time and money by using this technique of selecting samples for your study. As per its importance, this article aims to discuss different aspects of systematic sampling in detail.

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.