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The quality of research is dependent on the technique of gathering data. Any research topic aims to find the best result out of it. The obtained results help in making valuable decisions. There are many requirements of data in the case of research work. For example, it should be relevant as well as reliable. Also, you must be familiar with the different data collection methods suitable for the problem of study. The right selection of methods makes it possible to get the best results. An interview is one of the best and most commonly used methods of data collection. To get the most value from an interview, you must first understand the various techniques available. This article describes some of the most common approaches to data collection through interviews.

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.

A literature review aims to get insights related to the research problem and dive into the discussion. The structure of literature review is something that needs close attention. Without having a good structure, you cannot ace the milestones, and your literature review cannot stand out. The easiest way to structure literature review is using 5 Cs. These 5 Cs are comprised of cite, compare, contrast, critique, and connect. Each C has a particular set of attributes that help you make a perfect design to structure literature review. If any of the C is found to be missing in your literature review, I assure that you will have to resubmit it after

Data analysis is a practice that aims to make effective decisions after getting in-depth information related to any problem. The process of data analysis includes data collection, modelling and analysis. There are different methods of data analysis based on the type of research. The selection of a particular type of data analysis method is made based on the purpose of investigation. For example, the method of data analysis used for qualitative research is different from quantitative research. The methods used for quantitative research do not work well in qualitative research. Furthermore, the procedure of data analysis also has different steps that assist in finding the best results. As per its importance, this article aims to discuss different methods and procedure of data analysis in detail.

While working on a study, students often get confused in deciding whether they should write the context or background for their study. It is because they do not know the meaning of these terms and their differences. Because of this, they are unable to use them effectively. If you are facing the same thing, you do not worry about it because it is a common problem among students. However, you do not know about the similar and different aspects of context and background of study. It is because these two things are essential to attract readers to your research topic. This article will help you to understand the meaning and purpose of the context and background of study. Moreover, it will explain all the similarities and differences between them so that you will be able to use them perfectly in your study.

Data acquisition is the process of collecting data from a system or device for storage, analysis, assessment, and reporting. Data acquisition (DA) is responsible for setting up systems that collect real-time or historical data from equipment to measure their performance and to detect or anticipate problems. The data is collected in order to make documentation on assets, increase productivity, ensure regulatory compliance, and reduce costs of operation and maintenance. There are several types of data acquisition, but Data Warehouse and ETL systems get the most attention. Understanding what it does and does not is important to know. Here's a look at the different types along with some helpful software solutions to consider. This article will also help you understand what data acquisition is and why it's essential for companies

Data collection is the practice of gathering and measuring information on the variables of interest. Every research starts off with a set of pre-defined variables and research questions. Normally, the researchers collect two types of data to investigate the problem under study. One is called primary data collection, and the other is called secondary data collection. Both data collection methods employ different strategies and tools. Learning about those tools and techniques is essential for every researcher. Keeping its importance in view, today's guide is about tools and techniques being used worldwide for primary & secondary data collection. However, before jumping straight into those tools, let's define what data is and why it is necessary to collect it in research.

Have you ever felt that your emotions, experiences, and personal perceptions about a phenomenon create problems in the research process? If yes, then you know that you are bracketing in qualitative research. Qualitative research is about analysing a phenomenon, and the variables in this study are your control. If you introduce a change in the variables other than the natural one, you have bracketed your research. Initially, the term bracketing was solely related to phenomenological things, but now this has expanded to other qualitative research types. It is most common in observation and interview methods of qualitative research.

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.

Research is an important tool to open as many gates of knowledge as one needs to complete a dissertation. Dissertations mostly differ based on the niche, nature of problem statement, and tools or techniques selected to grab data. Search strategy

With the increasing use of artificial intelligence and automation, the way of doing things is changing in almost every sphere of life. Neural networks are also an integral part of this process. Working just like a human brain, this network is changing the world. Because of this, humans now do not have to do repetitive and time-consuming tasks. In this artificial intelligent world that is full of automation and deep learning technologies, these networks play a crucial role in solving complex problems and tasks using minimum time and money. This article can help you understand neural network analysis's most common uses and benefits.

Are you struggling to get all the material sorted for your research topic and unable to? Now you might be wondering where you went wrong. The main problem in these cases is that you have a broad topic covering various research areas. That is why you are unable to get your research sorted. Narrowing down a dissertation topic is required when writing a thesis statement. Your research topic must not be too broad as you will face many difficulties researching focused material. To narrow down your topic, you need to consider multiple factors. Research for a broad topic is a challenging task. Do not worry; this article will get you out of this predicament.

Research is an awful and dreadful process that demands a long-term commitment to unveiling the unknown facts to make the world a better place to live. Research allows researchers to pursue their interests, find something new, improve problem-solving skills, and hone challenge-taking skills. All these activities are important for a human to become an educated person in a real sense. Regardless of the discipline, almost every research has a unique motive that can be described under a few important categories. Furthermore, it is the purpose or motive of research that decides which method, technique, and tool will be more appropriate to conduct a particular research. This article is all about discussing moti