How To Write Significance Of The Study?

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How To Write Significance Of The Study
3. Describe how your research will help society – In this section, explain how your research will benefit society. Consider how the findings of your research will affect your community. For example, in the study on using lemongrass tea to lower blood glucose levels, your research will help the community understand the importance of lemongrass and other herbal plants.
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What is significance of the study example?

The significance of a study is its importance, It refers to the contribution(s) to and impact of the study on a research field. The significance also signals who benefits from the research findings and how.
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How do you present the significance of a study?

The significance of a study must be stated in the Introduction section of your research paper. While stating the significance, you must highlight how your research will be beneficial to the development of science and the society in general.
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What is the significance of the study in experimental research?

The Advantages –

Researchers have a full level of control in an experiment. It can be used in a wide variety of fields and verticals. The results are specific and conclusive. The results allow researchers to apply their findings to similar phenomena or contexts. It can determine the validity of a hypothesis, or disprove one. Researchers can manipulate variables and use them in as many variations as they desire without tarnishing the validity of the research. It discovers the cause and effect among variables. Researchers can further analyze relationships through testing. It helps researchers understand a specific environment fully. The studies can be replicated so that the researchers can repeat their experiments to test other variables or confirm the results again.

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What is the significance of the study for quantitative research?

The purpose of quantitative research is to generate knowledge and create understanding about the social world. Quantitative research is used by social scientists, including communication researchers, to observe phenomena or occurrences affecting individuals. Social scientists are concerned with the study of people.
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How to answer what is the significance of the study in defense?

Introduction Learn how to get prepared for your project defense with these common questions and tips Project defense can be very easy once you completely understand your research work and are prepared for the questions. During the defense, the panel of assessors will ask you questions to test your knowledge of the research subject matter, depth of your work, the results and conclusions you arrived at. How To Write Significance Of The Study Image Credit: Freepik Below are some of the likely questions you will be asked in a project defense room. Study these questions and suggested answers. You can also ask previous students in your department and your supervisor to guide you. Common project defense questions and answers 1.

  • Why did you choose this topic ? This might be the first question you will be asked, and you need to have a good response.
  • You should talk about the motivations for the study.
  • Talk about the research problem you wanted to address which made you embark on the study.2.
  • Briefly, explain what your research project is all about? To respond to this question, you need to fully understand your research project.

Basically, be able to repeat your abstract.3. What is the scope of the study Here you briefly state the specific aspects of your project topic that was covered.4. What is the significance of the study? To answer this question, you will need to state how your research work will help other researchers, educators, organizations(like the case study used), practitioners and policymakers.5.

Did you bridge any gap from your study? Here you should talk about how your study addressed the existing problems/concerns that made you carry out the research.6. What are your research variables? This question is asked in order to find out if you really know what your research project is all about. Explain your independent and dependent variable(s) to show them you really grasp the concept of your research topic.

Identify the variables in your project topic, define and explain them.7. What research methodology did you use? This is usually the chapter three of your project report. To respond to this question, you should briefly state the research design procedure you adopted for the research.

Talk about the data collection methods and sampling techniques employed in the research.8. Why did you use that research methodology? This is where you state the reason(s) for the choice of research methodology used. For example, if you used the survey research method, you can state reasons such as: no interviewer bias, cost-effective, it enabled you (the researcher) to collect information from the sample without influencing the population of the study e.t.c 9.

Why do you think your research is reliable? To answer this question, simply tell your audience/panel of assessors that the threats to research reliability (which are participants error, participant bias, research error, and researcher bias) did not occur during the research.

  • Or you can simply say that you made sure the threats were reduced to the barest minimum.10.
  • Why do you think your research is valid? To answer this question, simply tell your audience/panel of assessors that the findings from your study can be generalized to other relevant settings, group or case study.11.

In what way(s) does your research project contributes to knowledge? This question is similar to your significance of the study. You should talk about how your research is aimed at addressing a problem that was not addressed by previous researchers in your field of study.

You should also briefly state how your project will advance understanding in your research field.12. What are the limitations encountered No research project is perfect. It is common for at least one limitation to be identified. To answer this question, talk about the weaknesses that were out of your control.

You can talk about how weaknesses such as the short time frame for the research, lack of research studies/materials on the topic, lack of available data, the combination of lectures, exam and project research, limited sample size and selection, e.t.c impacted the analysis of your research data.13.

Which programming language did you use to write your program? (for computer science students) State the programming language and database used in the development of your software/program. If you did not design the program yourself or you were assisted by a friend or colleague, find out from the person which programming language was used.

You might also ask the person to give you a crash course on the programming language.14. Show us how your software works (for computer science students) Make sure you are familiar with how the software works. Also, be sure that there are no errors in the software.

Go ahead and show the panel of assessors how the software functions. You can also show them some records which you entered previously.15. What source of data was employed for the research? Here, you simply state the data collection methods that were used in the study. You should state if primary sources such as questionnaires, interview, observation OR secondary sources such as textbooks, journals, articles, e.t.c were used.

If you combined primary and secondary sources, briefly talk about it.16. What are your findings? Show the descriptive results from the study in a convincing and clear style. Make sure your findings refer to your research objectives/questions.17. Based on your findings what are your recommendations/suggestions? This is where you talk about the importance and implications of your findings from three levels namely: 1.

  1. Research (various ways other researchers can improve or refine the study) 2.
  2. Theory (the new contributions that you are adding to the body of knowledge) and 3.
  3. Practice (how the information gotten from your study can make practice better, improve the operational procedures, solve problems, improve policy making e.t.c).
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Note: Avoid the temptation to make recommendations that are not supported by your findings. Do not recommend based on your beliefs.18. What is the strongest point in your project? The duration of the defense might just be 10 – 15 minutes, as such the questioners will not have the time to ask you about every detail.

  1. They will want to focus on the major ideas and ask you the most important aspects of your research.
  2. Be ready to answer.19.
  3. If you could change something regarding your study, what would it be? The answer to this question can be gotten from the limitations of your study.
  4. You can give answers such as: 1.

Given the constraints (like the short time frame for the research or lack of sufficient funds) I was working with, this was what I was able to do but if I could do more, this is what I would have done.2. In doing this I learned a problem with this kind of data collection.

Next time, I will do it this way.20. What questions do you have for us You can ask them if there any revisions they want you to make in your report. Ask them to summarize the major revisions, so you can take some notes.21. Do you have any closing comments Thank the panel of assessors and let them know that the revisions/corrections that were given (such as rewriting the conclusion, tables/graphs that are not in the right format, something you said during the defense and they want you to include it in the report or some other issues they noticed you did not capture) would be implemented and shown to your supervisor.

In a project defense you are expected to: – Present yourself as a scholar in the discipline and an authority on your subject. – Cogently and clearly explain your work. – Have a conversation with the panel of assessors. – Defend any idea that might be disagreed upon.

That is why it is called a project defense). Project Defense tips 1. Be academically, mentally and physically prepared for your presentation.2. Practice, practice, practice. Rehearse several times with the equipment you will use for your presentation.3. Have a thorough understanding of the nature of your research problem.4.

Make eye contact with more than one member of the panel of assessors during the course of your presentation.5. Don’t speak too fast. Talk calmly with confidence.6. Bring a copy of your project report with you for reference. Learn more tips and tricks to ace your project defense
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What is significance in an experiment?

What Is Statistical Significance? – “Statistical significance helps quantify whether a result is likely due to chance or to some factor of interest,” says Redman. When a finding is significant, it simply means you can feel confident that’s it real, not that you just got lucky (or unlucky) in choosing the sample.

When you run an experiment, conduct a survey, take a poll, or analyze a set of data, you’re taking a sample of some population of interest, not looking at every single data point that you possibly can. Consider the example of a marketing campaign. You’ve come up with a new concept and you want to see if it works better than your current one.

You can’t show it to every single target customer, of course, so you choose a sample group. When you run the results, you find that those who saw the new campaign spent $10.17 on average, more than the $8.41 those who saw the old one spent. This $1.76 might seem like a big — and perhaps important — difference.

But in reality you may have been unlucky, drawing a sample of people who do not represent the larger population; in fact, maybe there was no difference between the two campaigns and their influence on consumers’ purchasing behaviors. This is called a sampling error, something you must contend with in any test that does not include the entire population of interest.

Redman notes that there are two main contributors to sampling error: the size of the sample and the variation in the underlying population. Sample size may be intuitive enough. Think about flipping a coin five times versus flipping it 500 times. The more times you flip, the less likely you’ll end up with a great majority of heads.

  1. The same is true of statistical significance: With bigger sample sizes, you’re less likely to get results that reflect randomness.
  2. All else being equal, you’ll feel more comfortable in the accuracy of the campaigns’ $1.76 difference if you showed the new one to 1,000 people rather than just 25.
  3. Of course, showing the campaign to more people costs more, so you have to balance the need for a larger sample size with your budget.

Managing Data Science An eight-week newsletter on making analytics and AI work for your organization. Variation is a little trickier to understand, but Redman insists that developing a sense for it is critical for all managers who use data. Consider the images below.

  • Each expresses a different possible distribution of customer purchases under Campaign A.
  • In the chart on the left (with less variation), most people spend roughly the same amount of dollars.
  • Some people spend a few dollars more or less, but if you pick a customer at random, chances are pretty good that they’ll be pretty close to the average.

So it’s less likely that you’ll select a sample that looks vastly different from the total population, which means you can be relatively confident in your results. Compare that to the chart on the right (with more variation). Here, people vary more widely in how much they spend.

The average is still the same, but quite a few people spend more or less. If you pick a customer at random, chances are higher that they are pretty far from the average. So if you select a sample from a more varied population, you can’t be as confident in your results. To summarize, the important thing to understand is that the greater the variation in the underlying population, the larger the sampling error.

Redman advises that you should plot your data and make pictures like these when you analyze the data. The graphs will help you get a feel for variation, the sampling error, and, in turn, the statistical significance. No matter what you’re studying, the process for evaluating significance is the same.

  • You start by stating a null hypothesis, often a straw man that you’re trying to disprove.
  • In the above experiment about the marketing campaign, the null hypothesis might be “On average, customers don’t prefer our new campaign to the old one.” Before you begin, you should also state an alternative hypothesis, such as “On average, customers prefer the new one,” and a target significance level.

The significance level is an expression of how rare your results are, under the assumption that the null hypothesis is true. It is usually expressed as a “p-value,” and the lower the p-value, the less likely the results are due purely to chance. Setting a target and interpreting p-values can be dauntingly complex.

  1. Redman says it depends a lot on what you are analyzing.
  2. If you’re searching for the Higgs boson, you probably want an extremely low p-value, maybe 0.00001,” he says.
  3. But if you’re testing for whether your new marketing concept is better or the new drill bits your engineer designed work faster than your existing bits, then you’re probably willing to take a higher value, maybe even as high as 0.25.” Note that in many business experiments, managers skip these two initial steps and don’t worry about significance until after the results are in.

However, it’s good scientific practice to do these two things ahead of time. Then you collect your data, plot the results, and calculate statistics, including the p-value, which incorporates variation and the sample size. If you get a p-value lower than your target, then you reject the null hypothesis in favor of the alternative.
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What is the significance of quantitative techniques?

What are the Quantitative Techniques of Decision Making? – While making a decision there are several Techniques that a manager of a company or an organization can employ. The quantitative Techniques help the manager to take decisions objectively and in an efficient way.

Linear Programming

This Technique helps in maximizing an object that is under limited resources. The main objective can be either optimization of a utility or minimizing of a disutility. In simple words, one can say that it helps in utilizing a resource or a constraint to its maximum potential.

Probability Decision Theory

Probability decision theory is a Technique that lies in the case, where the probability of an outcome can only be predicted. In simple words, one cannot always predict the exact outcome of any course of action. The managers use this approach to determine the probabilities of an outcome using the available information, firstly.

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The Game Theory

Often, the managers use certain quantitative Techniques only while making decisions pertaining to their business rivals. The game theory approach is one such kind of Technique. This Technique stimulates the rivalries or conflicts between businesses as a game.

Queuing Theory

Each and every business often suffers waiting for periods or queues pertaining to their personnel, equipment, resources, or services. For example, sometimes a manufacturing company may gather a stock of unsold goods due to irregular demands. This theory aims to solve such types of problems.

Stimulation

The stimulation Technique observes several outcomes under hypothetical or artificial settings. The managers try to understand how their decisions will work out under diverse circumstances. Then they finalize accordingly on the decision that is likely to be the most beneficial to them.

Network Techniques

All the complex activities often require concentrated efforts by the personnel in order to avoid the waste of time, energy, and also money. This Technique basically aims to solve by creating strong network structures for the work.

Mathematical Programming

Other than calculus, several other techniques can be used to solve decision-making issues. Mathematical programming is one such technique that can be used when several factors affect the choice of strategies. For example, if the aim is to reduce the total cost, no constraint can affect our choice of strategies.

If there are constraints, they might limit the funds which can be spent on the inventory, the space for inventory set up, or the highest number of orders that can be placed by the buyer or purchasing department. In this case, it can become an issue in constrained minimization. However, mathematical programming can be a solution for it.

The constraints form an environment where decision-makers can minimize or maximize the goals to be achieved. Constraint minimization and maximization is the best feature of mathematical programming. It is one of the most suitable frameworks for analyzing business problems.

Cost Analysis or Break-Even Analysis

All managers want to make profits. The objective of cost analysis or break-even analysis is to determine the break-even points or the optimum levels on which the profits are maximum. In decision-making, managers must pay attention to profit-making opportunities of alternative courses of action.

This requires that the cost of these alternatives must be assessed properly. A significant cost analysis is made between fixed and variable costs. A cost can be classified as fixed or variable in terms of the frequency of changes occurring in them at a particular period. However, in the long run, all costs are variable.

Fixed costs are those which remain constant irrespective of the production or sales. For instance, a manager’s salary will not change irrespective of the goods produced or sold out. On-road tax on a vehicle doesn’t change with its annual mileage covered.

Whereas, variable costs change with time. It highly depends on factors like the number of goods produced, sales in the financial year, or any similar factor. Some of its examples include sales commission concerning sales occurred, petrol prices in relation with distance traveled, labour wages based on hours worked, etc.

From a decision-making point of view, it is significant to know whether the cost will vary or not as a result of the decision. The total cost can be determined by adding the variable cost to the fixed cost of various levels of activity (for example, the number of items produced).

Cost-Benefit Analysis

It is a mathematical Technique for quantitative decision-making. This Technique is used to calculate the economic costs and the social advantages linked with a particular course of action. In this Technique, efforts are made to calculate the costs and benefits, not only for those that can be expressed in rupees but also the less effectively calculated outcomes of the decision.

Usually, this technique is used for making decisions on public projects in which social benefits, social costs, and actual out of the pocket costs are considered. Here, the cost analysis is associated with the economy of the entire society besides considering the benefits of individuals or a particular group.

The goal of this analysis is to get maximum profits for society. There are two most crucial quantitative Techniques under this approach. These include the Critical Path Method and the Programme Evaluation and the Review Technique. These techniques are effective because they segregate the work efficiently under the networks.
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What are the four good points of quantitative research?

The Four Main Concerns of Quantitative Research Quantitative researchers generally have four main preoccupations: they want their research to be measurable, to focus on causation, to be generalisable, and to be replicable. These preoccupations reflect epistemological grounded beliefs about what constitutes acceptable knowledge, and can be contrasted with the preoccupations of researchers who prefer a qualitative approach.

  • It may sound like it’s stating the obvious – but quantitative researchers are primarily interested in collecting numerical data, which means they are essentially concerned with counting social phenomena, which will often require concepts to be operationalised.
  • Causality
  • In most quantitative research there is a strong concern with explanation: qualitative researchers are more concerned with explaining why things are as they are, rather than merely describing them (which tends to be the focus of more qualitative research).
  1. It follows that it is crucial for quantitative researchers to effectively isolate variables in order to establish causal relationships.
  2. Generalisation
  3. Quantitative researchers tend to want their findings to be representative of wider populations, rather than the just the sample involved in the study, thus there is a concern with making sure appropriate sampling techniques will be used.
  • Replication
  • If a study is repeatable then it is possible to check that the original researchers’ own personal biases or characteristics have not influenced the findings: in other words, replication is necessary to test the objectivity of an original piece of research.
  • Quantitative researchers tend to be keen on making sure studies are repeatable, although most studies are never repeated because there is a lack of status attached to doing so.

Source: Bryman (2017) Social Research Methods : The Four Main Concerns of Quantitative Research
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What is the difference between justification and significance in research?

Can you tell me the difference among ‘significance,’ ‘justification,’ and ‘need’ of the study with real-life examples? | Editage Insights 1 Answer to this question Hello Abdulkadir – Welcome to the forum! Although all three terms seek to explain why the study in question was undertaken and – at least to us – can be used interchangeably, we can distinguish some differences in the shades of their meaning.

‘ Significance ‘ relates to the importance of the study; ‘ justification ‘ (also called ‘rationale’) implies that some readers may not see its importance and therefore some explanation is expected; and ‘ need ‘ is used to point out any practical difficulty or problem for which a solution is required.

As you asked for real-life examples, here is a paper that uses the word significance in its title: ‘Endometrial polyps during menopause: characterization and significance.’ The abstract shows why: “Postmenopausal endometrial polyp is a common, mostly benign entity,

However, the relatively high rate of concomitant endometrial hyperplasia, especially in patients receiving hormone replacement therapy, dictates a thorough histological evaluation.” Here is a paper that uses the word justification in its title, and an excerpt from the abstract shows why. The title is ‘Menopause-related affective disorders: A justification for further study,’ and the abstract begins thus: “Despite descriptions dating back to the 19th century of menopause-related affective syndromes, researchers have been unable to characterize a specific disturbance of mood or behavior related to this period of life.

Methodologic problems in earlier studies are identified, and it is suggested that further study is warranted.” Clearly, the author expected reviewers to question the need for such a study and therefore provided a justification. Lastly, here is a paper that questions the need to sacrifice sleep for academic achievements.

However, as you can see for yourself, these words in the titles could have been replaced with their synonyms without any significant changes in the intended meaning. Hope the confusion is sorted out now. 🙂 For more insights and information into these concepts on our site itself, you may refer to the following resources: And as these are written in the Introduction section (as you have mentioned too), you may find this handbook helpful: Finally, as you are probably writing a paper presently, or planning one, all the best for that!

: Can you tell me the difference among ‘significance,’ ‘justification,’ and ‘need’ of the study with real-life examples? | Editage Insights
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What is the significance of the thesis?

How to write the significance of the study in a thesis? The introduction chapter of the thesis contains the section “significance of the study”. As the name clearly indicates, its primary purpose is to explain the primary contributions of the thesis. Thesis significance is essential in the introduction because it indicates the relevance of the work, potential outcomes and the major beneficiaries of the study.

  • General contribution of the study.
  • Specific contribution and application of study.
  • Grounds on which the study is based.
  • Explain with logical reasons the benefits of the study.

The significance of the study is a way through which the researcher conveys to the reviewer how the thesis is unique. It could be for the reviewer of the thesis, peer review by an academician, publication on various platforms, or to apply for a research grant. A clear statement of the thesis significance and its contribution gives the reader information about the research purpose too.
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How do you know if data is significant?

Understanding Statistical Significance – The calculation of statistical significance (significance testing) is subject to a certain degree of error. Even if data appear to have a strong relationship, researchers must account for the possibility that an apparent correlation arose due to random chance or a sampling error,

Sample size is an important component of statistical significance in that larger samples are less prone to flukes. Only randomly chosen, representative samples should be used in significance testing. The level at which one can accept whether an event is statistically significant is known as the significance level.

Researchers use a measurement known as the p-value to determine statistical significance: if the p-value falls below the significance level, then the result is statistically significant. The p-value is a function of the means and standard deviations of the data samples.

  • The p-value indicates the probability under which the given statistical result occurred, assuming chance alone is responsible for the result.
  • If this probability is small, then the researcher can conclude that some other factor could be responsible for the observed data.
  • The opposite of the significance level, calculated as 1 minus the significance level, is the confidence level.

It indicates the degree of confidence that the statistical result did not occur by chance or by sampling error. The customary confidence level in many statistical tests is 95%, leading to a customary significance level or p-value of 5%. “P-hacking” is the practice of exhaustively comparing many different sets of data in search of a statistically significant result.
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What are the items of significance?

Certain objects come to have special significance – not just for some individuals, or for brief periods of time, but for generations and for whole societies. Some of these objects are believed to hold spiritual powers, so that ancestors, or spirits, speak through them.

Other are thought to have healing powers. Some may be significant because they commemorate or date back to a great event in the history of a particular culture. Some objects are symbolic. They stand for, or in place of, something that is important to the community, something non-physical – a deity, perhaps.

How To Write Significance of the Study l Step by step guide With Examples

Still others may be thought to possess the power of divination – of explaining something hidden from daily knowledge, or of foretelling the future. Objects like these may be kept for use only on special days, or only by certain people, like priests or shamans.
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What is the p-value for statistical significance?

P-Value And Statistical Significance: What It Is & Why It Matters When you perform a statistical test a p -value helps you determine the significance of your results in relation to the null hypothesis. The (H0) states that there is no relationship between the (one variable does not affect the other).

  • It states the results are due to chance and are not significant in terms of supporting the idea being investigated.
  • Thus, the null hypothesis assumes that whatever you try to prove did not happen.
  • The alternative hypothesis (Ha or H1) is the one you would believe if the null hypothesis is concluded to be untrue.

The alternative hypothesis states that the independent variable did affect the dependent variable, and the results are significant in terms of supporting the theory being investigated (i.e., not due to chance). A p-value, or probability value, is a number describing how likely it is that your data would have occurred by random chance (i.e.

  • A p -value less than 0.05 (typically ≤ 0.05) is statistically significant. It indicates strong evidence against the null hypothesis, as there is less than a 5% probability the null is correct (and the results are random). Therefore, we reject the null hypothesis and accept the alternative hypothesis.
  • However, if the p -value is below your threshold of significance (typically p < 0.05), you can reject the null hypothesis, but this does not mean that there is a 95% probability that the alternative hypothesis is true.
  • The p -value is conditional upon the null hypothesis being true but is unrelated to the truth or falsity of the alternative hypothesis.
  • A p -value higher than 0.05 (> 0.05) is not statistically significant and indicates strong evidence for the null hypothesis. This means we retain the null hypothesis and reject the alternative hypothesis. You should note that you cannot accept the null hypothesis; we can only reject it or fail to reject it.
  • A statistically significant result cannot prove that a research hypothesis is correct (which implies 100% certainty).Instead, we may state our results “provide support for” or “give evidence for” our research hypothesis (as there is still a slight probability that the results occurred by chance and the null hypothesis was correct – e.g., less than 5%).

The observed value is statistically significant (p ≤ 0.05), so the null hypothesis (N0) is rejected, and the alternative hypothesis (Ha) is accepted. The 6th edition of the APA style manual (American Psychological Association, 2010) states the following on the topic of reporting p-values: “When reporting p values, report exact p values (e.g., p =,031) to two or three decimal places. However, report p values less than,001 as p <,001. The tradition of reporting p values in the form p <,10, p <,05, p <,01, and so forth, was appropriate in a time when only limited tables of critical values were available." (p.114) View complete answer

How do you answer a research defense?

1. What is your topic, and why did you choose it? – Give a quick summary in just a few sentences on what you’ve researched. You could certainly go on for hours about your work, but make sure you prepare a way to give a very brief overview of your thesis. Then, give a quick background on your process for choosing this topic.
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What to say if you don t know the answer in a defense?

What can I do to ensure that my thesis defense is successful? | Editage Insights 1 Answer to this question Getting cold feet or being nervous is normal before your defense. However, preparing well in advance for your defense and going through prcatce sessions can help you feel more confident. Here are a few things you can do before your thesis defense: 1.

  • Make sure you know your thesis well and are sure about the evidence you are going to present in order to defend your thesis.
  • Make sure you go through all your material several times before the actual defense so that you know your material thoroughly.2.
  • Try to anticipate at least 10 questions that your professor can ask and keep the answers to these questions ready.

Go through these a few times before your defense.3. Have a few practice sessions with your friends and/or family. This will help you feel more confident. On the actual day of the defense, try to be calm and keep a clear mind. Think through before you reply.

It is okay to request your teachers to repeat their question and take a few seconds before you respond. If you have prepared well, you should be able to answer. If there is a question that you do not know the answer to, it is okay to say “I don’t know, but that is an interesting question because XYZ.” Sometimes, teachers will ask questions for you to think out-of-the-box.

But, you are not expected to know everything. Keep in mind that you know more about your work than anyone else in that room, that you are the expert, the one with the most knowledge on your thesis subject! You are so close to getting that degree. Good luck! Related reading: : What can I do to ensure that my thesis defense is successful? | Editage Insights
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