Research questions and hypotheses are two distinct approaches to understanding a particular phenomenon. Research questions are the empirical questions that can be answered by collecting data through observation or experimentation. Hypothesis, on the other hand, is an educated guess about how something works or what it is like.

The purpose of research is to understand a phenomenon, process or outcome. It is not an end in itself. The purpose of research is to answer a question or solve a problem. Research questions are statements that describe the problem you want to investigate. The question should be specific enough so that it can be answered by the method used in the research study.The hypothesis is the main point of interest that guides your research. It is what you think will happen (example: if your research participants respond as you expect them to respond), which makes it important to consider carefully in your choice of study design and methods.

A research question is a statement about what you want to find out. It describes the purpose of the research. For example, “What factors influence the success of a new product?” or “How does a video game affect players’ cognitive abilities?” A hypothesis is an idea that might be true but has not yet been proven. It is based on observations and previous knowledge. If a researcher wants to find out whether playing violent video games increases aggression, they might develop a hypothesis like this: “Violent video games increase aggression”. This can be tested by measuring aggression in people who have played violent video games and comparing it with aggression in people who have not.

The role of research questions in research study is to provide a focus for the researcher’s efforts, which may be used to develop and guide the research. The researcher may use a variety of approaches such as qualitative, quantitative and mixed methods in order to answer questions that he/she believes will lead to significant findings. This will help the researcher in developing an appropriate research design for answering his/her research question(s).

Hypothesis is an educated guess about how something works or what it is like. It provides a framework for conducting research by providing a testable prediction about the outcome of interest. A hypothesis can be either specific or general; however general hypotheses are more useful because they give researchers a way to organize their thoughts and outline their ideas more clearly before conducting tests on specific cases.

Hypothesis v/s Research Question

• A hypothesis is a proposed explanation for a phenomenon. In research, we usually frame a hypothesis around a research question. A hypothesis, however, is more broad and abstract. A hypothesis is an educated guess about what might happen. The hypothesis is not concrete; it’s just a theory. A hypothesis does not have an “if/then” format like an observation does. 
• A hypothesis may be stated as “if X happens then Y will happen,” where X and Y are variables whose values can fit into one of two categories (e.g., “If participant A responds positively when asked how his job performance has improved, then he will also respond positively when asked whether he has improved his job performance”). A null hypothesis states that there is no difference between two variables (X1 and X2). A directional hypothesis specifies that there is an effect behind one variable but not behind another variable (X1 vs. X2 vs. Y).
• A research question is the question that you want to answer through your research. It’s the topic that you choose to investigate, not the method you choose to investigate it. 
• A research question is what you investigate and why you want to investigate it. Your research question can be phrased in many ways. 
• For example, if you want to study how people use social media, your question could be: “What are the key trends that people are using social media for?”, “What social media platforms are being used most often?”, “How are people using social media?”, “What are the benefits of using social media?”, and so on. 
• Your research question guides the type of research that you do. For example, if you want to know what social media platforms people are using most often, then your research question guides the method that you use, such as an online survey. Your research question determines what questions you ask, what answers you look for, and how you present your findings.
• There are many ways to formulate a research question, and it can be hard to figure out what kind of question will yield the best results. When you’re conducting research, it can be easy to fall into the trap of thinking that a research question is a hypothesis. In some cases, though, a research question is not a hypothesis at all; instead, it’s more of an observation. For example, when you read journal articles, you may come across research that simply looks at data. This type of research does not have a hypothesis; instead, it’s an observation about the data. All that’s being examined is the data itself, not why it happened, what it means, or how it can help solve a problem.
• A hypothesis is a proposed explanation for a phenomenon. A research question is what you want to investigate and why you want to investigate it.

Your research question and hypothesis should be stated in the introduction and addressed again in the conclusion to demonstrate that you have completed what you set out to do and that you have not lost sight of your objective throughout your research process.

Preparing a research document is a time-consuming, tedious process and includes various stages. One has to consider several aspects like availability and access to sources, contents to be included in the research document, etc while writing down a research document. Chapters in research document often demand undivided attention from the research scholar, one such being, the ‘methodology’ chapter. 

Methodology section provides a clear idea of your research and its validity & reliability. Since methodology chapter can make an everlasting impression on readers, it has to be crafted in an effective manner. Typically, a research methodology chapter should be written by following a model to make it comprehensible for readers. Today, most of the Universities are demanding scholars to follow ‘research onion’ model while writing down this section. Has your University asked you to follow this model? Sounds like a complex process?

To ease your life, we, with the help of writers providing PhD synopsis writing service have figured out and have explained each layer of this model. 

Research onion model, based on the philosophies of ontology, epistemology, and axiology is segregated into research philosophy, approaches, strategy, time horizons and data collection approaches.

• Research philosophy –  This determines the approach used to collect infer and utilise a certain set of data for your research work and to do so, you can select philosophies like  realism, positivism, and interpretivism. No matter which philosophy use have chosen, it must perfectly align your research objective and your choice of philosophy must be justified.

• Research approach – Research approach includes inductive and deductive methods and determines the logical reasoning. Choose one among the approaches as per your needs. The inductive approach lets you form a novel theory based on the data collected, whereas the deductive approach lets you ensure if the collected data holds good with the existing theories.

• Research strategy –  Research strategy consists of the source and nature of the data which has been collected to meet the objectives of your research. Based on nature, the data can be qualitative or quantitative. Whereas, based on the source, the data can either be primary or secondary. 

• Time horizon –  Time horizon is of two types cross-sectional and longitudinal study. These  give an idea of the exact timeline in which the research work has been conducted. 

• Data collection –  Data collection highlights the underlying techniques used by you to collect the necessary data for conducting your research. You should specify the statistical tools/software that you have exploited and approaches that you have followed while gathering the required data. This section of the research onion, lets you decide the content of the questionnaire sample groups. It is a must for you to ensure that all the tools and decisions you have used syncs with the philosophies.

Writing a methodology section is definitely a tough nut to crack. If you are facing tough time in writing this section, then seek professional help from writers offering PhD synopsis writing service. 

Experimental research design is widely used by the research community to manipulate one or more variables (independent) and determine their effect on the other variables (dependent). This type of research design is often used in two cases: (1) When time priority exists in a causal relationship and (2) there exists a consistency in a causal relationship. 

Experimental research design is classified into a pre-experimental, true experimental and quasi-experimental research design. Although true experimental design is regarded as the most accurate design, it is a quasi-experimental design that is widely used in the research in social science, psychology, etc. as it doesn’t involve random assignment of participants to orders of condition. 

A quasi-experimental research design, also known as ex-post-facto design involves the selection of groups without a random pre-selection process. This type of research design doesn’t allow the research scholar to control the assignment of participants to groups or conditions. It identifies a comparison group that is similar to the intervention group in terms of baseline features. 

Types of quasi-experimental research designs 

Quasi-experimental research designs are of various types and have a variety of applications in a specific framework. 

• Non-equivalent group, posttest only design – This type of research design includes administration of outcomes measures to treatment group or two groups and a comparison. For instance,  a group of students might receive coding instruction using the latest programming language whereas another group of students might receive writing instruction using standard programming language. After a week, a writing comprehension test is administered to determine which programming language is more effective. However, the major setback of this design is that the two selected groups may differ in important ways that impact the writing process. For example, if a group of students who code using standard programming language, then we cannot determine if the students are well-prepared or if it’s the result of utilization of standard programming language.

• Non-equivalent control group design – Here we compare the control group and the experimental group. The groups are selected & assigned through convenience rather than choosing via randomization. But the problem arises when the results of the control and experimental group are to be compared. For instance, a researcher wants to determine the impact of online training on the average grade point of class 11 students. Here the researcher cannot randomly collect the participants as the institution will not permit to regroup the classes. Therefore, the researcher chose two sections of class11 from the same institution. Since the participants were not randomly allocated, the researcher cannot conclude that two groups were equivalent before the manipulation. Also, it cannot be determined if the difference in the grade point is only due to the impact of online training as other variables such as intelligence, motivation, etc. can bring about the difference in learning.

• Separate pretest-posttest sample design – The main idea of this research design is that the individual selected for the pretest is not the same as that of the posttest. For example, assume that the two companies are similar. You can use one company to implement your study and second company as a control. A customer satisfaction program is developed. Initially, the customer satisfaction is measured without implementing the program. This is followed by the implementation of program and measuring the client satisfaction. Here the clients for each company will be different for pretest and posttest. The response of the client from the pretest and posttest cannot be compared. As a result, nonequivalence exists not just between companies but also between the pre and post groups.

•  Double pretest design – This type of quasi-experimental research design is regarded as the strongest design with respect to internal validity. This is because, in the pre-post nonequivalent research design, the nonequivalent groups may differ from one another. Pretest does not tell us if the changing at the same rates prior to the program. But with a double pretest design, we can determine the rate of change through pretest1 and pretest2. Therefore, this research is explicitly used to control the selection of maturation threat. 

• Repeated treatment design – Here the treatment is withdrawn and then presented for the second time. Simply said, treatment is presented more than once. The response of the participant is measured prior to and after the implementation of treatment. The treatment program is withdrawn and then the process is performed again. Consider an example where the government has banned the consumption of alcohol. To analyze the impact of this policy, problems pertaining to alcohol consumption were assessed. The outcome of the policy was the health of individuals improved as a result of the ban. 

A quasi-experimental design is widely used to produce results for general trends. The added advantage of this design is that it doesn’t require randomization, prescreening and minimizes the threat to internal validity. 

Although this type of research design is easy to implement, one should take care to address the internal validity threat and utilization of additional data.