6 Steps to Compose a Professional Masters Research Proposal

6 Steps to Compose a Professional Masters Research Proposal 6 Steps to Compose a Professional Masters Research Proposal If you have completed your undergraduate studies, and you are interested in undertaking further studies to advance your academic career and qualifications, then the next stage of your assessment may include a master’s research proposal. What Is a Master’s Research Proposal? A master’s research proposal aims to demonstrate that you have identified a research subject that is worthy of investigation and study. It is also essential that you demonstrate that the research subject that you are considering is something that is manageable within the timescale that you would have available. The criteria that you need to consider is that your proposed research project would make a significant contribution to the understanding of that subject or the field in which you are studying. In this article, we will walk through some of the key elements that you need to include or consider in your master’s research proposal. Step 1 Title While at this stage of the process, the title that you give your research proposal is provisional only, it is important that you are clear and concise in your title, make sure that the reader can immediately understand the subject that you are proposing to study. Step 2 Introduction In the introduction, you should immediately highlight the questions that are central to the research that you are proposing. You need to be able to articulate the contribution that your research will make to the chosen field of study. Step 3 Background In this ‘background’ section, you are essentially taking the questions that you identified in your introduction and expanding on them, giving more depth and context. Try and set out your research questions in as much detail as possible. Explain to the reader the specific areas that are going to be exploring and why it is important that these areas are explored. Reinforce the contribution that this research will make to your academic discipline. Step 4 Research In this section, you need to set out the research methods that you will be using in this piece of work. Detail the sources that you intend to use, detail the analysis that you will need to complete. Also, make it clear where you are going to access the information that you need. Ensure that you are able to explain how this research is going to help you answer the research questions that you have identified in the introduction. Step 5 Schedule This part of your paper is particularly important for demonstrating that you have considered whether this project is manageable within the time period that you have available. This type of masters research is expected to take three or four years. Map out the work involved and demonstrate how you will be able to deliver your research within the time available. Step 6 Bibliography Any reference points that you have used in this proposal need to be properly documented in the bibliography part. This is the basic academic practice. Use a standard bibliography format that is accepted by your academic institution. A successful Master’s research proposal is an important step when taking your academic studies to the next level. Make sure that you consider all of the different requirements and give yourself the best chance for success.

Type I vs. Type II Errors in Hypothesis Testing

Type I vs. Type II Errors in Hypothesis Testing The statistical practice of hypothesis testing is widespread not only in statistics but also throughout the natural and social sciences. When we conduct a hypothesis test there a couple of things that could go wrong. There are two kinds of errors, which by design cannot be avoided, and we must be aware that these errors exist. The errors are given the quite pedestrian names of type I and type II errors. What are type I and type II errors, and how we distinguish between them?  Briefly: Type I errors happen when we reject a true null hypothesisType II errors happen when we fail to reject a false null hypothesis We will explore more background behind these types of errors with the goal of understanding these statements. Hypothesis Testing The process of hypothesis testing can seem to be quite varied with a multitude of test statistics. But the general process is the same. Hypothesis testing involves the statement of a null hypothesis and the selection of a level of significance. The null hypothesis is either true or false and represents the default claim for a treatment or procedure. For example, when examining the effectiveness of a drug, the null hypothesis would be that the drug has no effect on a disease. After formulating the null hypothesis and choosing a level of significance, we acquire data through observation. Statistical calculations tell us whether or not we should reject the null hypothesis. In an ideal world, we would always reject the null hypothesis when it is false, and we would not reject the null hypothesis when it is indeed true. But there are two other scenarios that are possible, each of which will result in an error. Type I Error The first kind of error that is possible involves the rejection of a null hypothesis that is actually true. This kind of error is called a type I error and is sometimes called an error of the first kind. Type I errors are equivalent to false positives. Let’s go back to the example of a drug being used to treat a disease. If we reject the null hypothesis in this situation, then our claim is that the drug does, in fact, have some effect on a disease. But if the null hypothesis is true, then, in reality, the drug does not combat the disease at all. The drug is falsely claimed to have a positive effect on a disease. Type I errors can be controlled. The value of alpha, which is related to the level of significance that we selected has a direct bearing on type I errors. Alpha is the maximum probability that we have a type I error. For a 95% confidence level, the value of alpha is 0.05. This means that there is a 5% probability that we will reject a true null hypothesis. In the long run, one out of every twenty hypothesis tests that we perform at this level will result in a type I error. Type II Error The other kind of error that is possible occurs when we do not reject a null hypothesis that is false. This sort of error is called a type II error and is also referred to as an error of the second kind. Type II errors are equivalent to false negatives. If we think back again to the scenario in which we are testing a drug, what would a type II error look like? A type II error would occur if we accepted that the drug had no effect on a disease, but in reality, it did. The probability of a type II error is given by the Greek letter beta. This number is related to the power or sensitivity of the hypothesis test, denoted by 1 – beta. How to Avoid Errors Type I and type II errors are part of the process of hypothesis testing. Although the errors cannot be completely eliminated, we can minimize one type of error. Typically when we try to decrease the probability one type of error, the probability for the other type increases. We could decrease the value of alpha from 0.05 to 0.01, corresponding to a 99% level of confidence. However, if everything else remains the same, then the probability of a type II error will nearly always increase. Many times the real world application of our hypothesis test will determine if we are more accepting of type I or type II errors. This will then be used when we design our statistical experiment.