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Hypothesis testing is an important activity performed in engineering, statistics, and practice-based medicine. Basically, in this testing, the researcher tests a pre-defined hypothesis and tries to uncover the relationship between two variables. An answer to this test is the half solution to any research question. Therefore, you must do it with care. However, there are normally two types of errors that you can encounter while doing this testing. Those are type I and type II hypothesis errors. Do you not know about these errors? Okay, no worries because today's article defines, gives causes and explains

As a researcher, you must understand in-depth quantitative research and its types to apply it in your research. It is a way of collecting and evaluating numerical data to answer the research question or test the hypothesis. Quantitative research is different from qualitative research as it identifies the correlations within the numbers. Qualitative research, on the other side, is used to evaluate non-numerical data. When your topic of research is about to solve statistically, then you move towards quantitative research to identify the facts, use numerical data and compare it to prove or disprove the hypothesis and generate statistical results.

Abduction is a different form of scientific inference appropriate for quantitative research. Charles Peirce was an advocate of abductive approach in research. Peirce considered abduction approach the catalyst for theory discovery. It is the most inventive and flexible scientific logic compared to deduction and induction. Researchers must develop a hypothesis on probation. Researchers use abduction when they come across anomalies in relation to accepted hypotheses. Abduction is the term used to describe this innovative stride.

The abstract of doctoral dissertation is an integral component of the document. It provides a brief overview of the problem or hypothesis being researched and describes how you approached your research and study setting. The abstract also includes a thorough description of how you collected your data and analyzed it as well as its significance within the field. Your results will speak directly to whether or not your dissertation topic was interesting enough to research in-depth or if it would be better suited for another type of project altogether.

Data collection is a systematised way to collect relevant information for a particular problem. In research work, data is collected to get the in-depth information to evaluate a specific aspect. In some research, you have to collect data to test a hypothesis. On the other hand, there can be a research question to address. In both cases, you have to do an analysis that requires data. Otherwise, it remains impossible to provide support to the conclusion of the study. Research always demands evidence for every claim. Without evidence, your effort, time, and investment are not worth it. So, you have to be very clear about each aspect of the research work. From one purpose to another, you can find a variety of data types. It can be in numeric as well as subjective forms.