Research Methodology

Research in research methodology is significant as it provides the framework and guidelines for conducting systematic investigations, ensuring that the findings are reliable, valid, and credible. It helps researchers design studies, collect and analyze data, and draw conclusions in a systematic and rigorous manner. Research methodology also guides researchers in choosing the appropriate methods and tools to address specific research questions or problems.

Convenience sampling runs the greatest risk of collecting unrepresentative evidence, as it involves selecting participants based on their ease of access rather than their representativeness of the population. This method can lead to biased results and limit the generalizability of findings to the larger population.

Surveys are a common research method used to gather information about individuals' behaviors, attitudes, and opinions. Researchers design questionnaires or interviews to collect data from a sample of the population in order to study these aspects. Surveys can provide valuable insights into people's thoughts and behaviors on a wide range of topics.

Field setting research methodology is a type of research that involves collecting data in a natural environment, such as a workplace or community, rather than in a controlled laboratory setting. This approach allows researchers to observe and study phenomena as they naturally occur, providing a more realistic understanding of the subject of interest. Field setting research often involves direct engagement with participants to gather data through interviews, surveys, or observations.

Freud primarily used case studies and introspection, along with the technique of free association, in his research. He emphasized the importance of exploring the unconscious mind to understand behavior and personality development.

One type of qualitative research uses anecdotal evidence. Anecdotes are personal accounts/thoughts/feelings. This type of evidence cannot be generalized but can pave the way for further research.

You can find these papers online to help come up with ideas. A simple keyword search can help you find the papers that you want.

One example of a methodology in a report could be a research design that outlines how data was collected, analyzed, and interpreted to address the research questions. This can include details on the sampling technique, data collection methods (e.g., survey, interviews, observations), data analysis techniques, and any tools or software used in the process. The methodology section should provide enough information for others to understand and potentially replicate the study.

Strengths: Natural observation allows researchers to study behavior in real-world settings, providing a more authentic representation of cognitive processes. It also allows for the study of behaviors that may not be easily replicated in a laboratory setting.

Weaknesses: Natural observation can be prone to observer bias and lack of control over extraneous variables. It may also be challenging to ensure the privacy and consent of individuals being observed, and the data collected may be harder to quantify and analyze compared to controlled experiments.

Method is a particular way of solving a specific problem. it is therefore unlikely that your research will just have 'a method' as the whole research will probably draw on different ways (methods) of proving/solving discrete aspects of the research. Methodology, therefore, means the collection of methods you used in a particular piece of research. However, N.B.! The term methodology is confusing, because it can often be used to refer to the underlying 'methodology' (or ideology/principles/set of beliefs) which led you to opt for one set of methods rather than another. E.g. if you believe that number crunching does not come up with worthwhile results, you will go for indepths interviews etc. that is part of your 'methodology' and it's based on your assumptions/mindset

Researchers use experiments because they allow for cause-and-effect relationships to be established between variables. Experiments provide a high level of control over variables, which increases the internal validity of the study. This method helps researchers test hypotheses and make inferences about the relationship between variables.

Researchers use experiments to distinguish between cause and effect relationships. This involves manipulating one variable (independent variable) and observing the effect on another variable (dependent variable) in a controlled setting. Experiments allow researchers to make direct inferences about the relationship between variables, which is difficult to achieve with other research methods.

how does experimental research differ importantly from correlational research methods

Correlational Research are predictions and are mostly based on statistics. Whereas Experimental Research is based on experiment and explaination.

Qualitative research methods allow for in-depth exploration of complex phenomena, providing rich and detailed data that can uncover underlying motivations and behaviors. They are flexible and adaptable, allowing researchers to adjust their approach based on emerging findings. Qualitative methods are well-suited for generating new hypotheses and theories that can guide further research.

give some examples of descriptive reseach titles give some examples of descriptive reseach titles

A randomized controlled trial with a control group that does not smoke cigarettes would provide the best way to assess if cigarette smoking boosts mental alertness. This method would help establish a cause-and-effect relationship between smoking and mental alertness by controlling for other variables that could influence the results. Additionally, cognitive tests before and after smoking could be used to measure mental alertness objectively.

Common research methods include experiments, surveys, interviews, observations, case studies, and content analysis. Each method has its own strengths and limitations, and researchers choose the most appropriate method based on their research question and goals.

A quasi-experimental research design is a type of research methodology that lacks full experimental control but still allows for comparison between groups. It involves manipulating an independent variable to observe its impact on a dependent variable, but lacks random assignment to groups. This design is often used when true experimentation is not feasible or ethical.

Qualitative research method involves studying and understanding human behavior, thoughts, and emotions by collecting and analyzing non-numerical data such as interviews, observations, and text analysis. It aims to explore and interpret participants' subjective experiences to gain insights and deepen understanding of a particular topic or phenomenon.

Interesting question, as many have the impression that both are same. However, both are two separate concepts with an entirely different meaning. The primary difference between the two is that Research methods is the method using which you carry on your research with regards to a particular topic whereas Research methodology is a logical explanation of these methods.

Research methods may include using experiments, surveys and tests used to conduct research. On the other hand, Research methodology includes critical study of different techniques using which a research can be conducted. In short, research method is about solving a given problem whereas research methodology deals with finding solutions to solve a particular problem.

this method provides an explanation about the extent of relationship between two or more variables. it examines the relationships including similarities or differences among several variables.

A research methodology defines what the activity of research is, how to proceed, how to measure progress, and what constitutes success. AI methodology is a jumbled mess. Different methodologies define distinct schools which wage religious wars against each other. Methods are tools. Use them; don't let them use you. Don't fall for slogans that raise one above the others: ``AI research needs to be put on firm foundations;'' ``Philosophers just talk. AI is about hacking;'' ``You have to know what's computed before you ask how.'' To succeed at AI, you have to be good at technical methods and you have to be suspicious of them. For instance, you should be able to prove theorems and you should harbor doubts about whether theorems prove anything. Most good pieces of AI delicately balance several methodologies. For example, you must walk a fine line between too much theory, possibly irrelevant to any real problem, and voluminous implementation, which can represent an incoherent munging of ad-hoc solutions. You are constantly faced with research decisions that divide along a boundary between ``neat'' and ``scruffy.'' Should you take the time to formalize this problem to some extent (so that, for example, you can prove its intractability), or should you deal with it in its raw form, which ill-defined but closer to reality? Taking the former approach leads (when successful) to a clear, certain result that will usually be either boring or at least will not Address the Issues; the latter approach runs the risk of turning into a bunch of hacks. Any one piece of work, and any one person, should aim for a judicious balance, formalizing subproblems that seem to cry for it while keeping honest to the Big Picture. Some work is like science. You look at how people learn arithmetic, how the brain works, how kangaroos hop, and try to figure it out and make a testable theory. Some work is like engineering: you try to build a better problem solver or shape-from algorithm. Some work is like mathematics: you play with formalisms, try to understand their properties, hone them, prove things about them. Some work is example-driven, trying to explain specific phenomena. The best work combines all these and more. Methodologies are social. Read how other people attacked similar problems, and talk to people about how they proceeded in specific cases.