Dissertation Research

If you are a doctoral student who is starting your dissertation, you have no-doubt been told that you need to perform dissertation research before you begin the statistics portion of your dissertation. What this means, essentially, is that you need to perform dissertation research before you begin the lengthy process of gathering data and interpreting that data. Much like the gathering of data and the interpretation of that data, dissertation research can also be a very lengthy process. In dissertation research, you must check to see if what you want to study has been studied before. Because a dissertation must provide new information to the subject field, it is vitally important that you check to see if what you want to study has been studied before. If your dissertation research is not extensive, than that dissertation research might lead you to believe that your topic of study is new and that your exact topic has never been studied before. If indeed it has been studied before, then your dissertation will not be providing new information to the subject field, and therefore your dissertation will not be accepted and will not grant you the doctoral degree you are seeking.

It is very important, then, that the dissertation research that you perform is accurate and extensive. This can indeed take much time, but it is important to do the dissertation research thoroughly. It is important to note that your topic does not have to be entirely new and never-before tested and studied. Rather, your dissertation must simply provide some new information about that topic. Thus, when you conduct your dissertation research, you should be checking to see if there are any gaps in the existing knowledge. You could perform your dissertation so that it addresses those gaps, and thus your dissertation would be accepted.

As you do your dissertation research, it is very important that you document everything that you read, study, reference and analyze. This is because part of your dissertation research and dissertation will involve a literature review. A literature review documents all that you have read and studied in your dissertation research. Additionally, a literature review synthesizes all of the information obtained in the dissertation research. Because your dissertation research will be very, very extensive, you will come across all kinds of information in your dissertation research. This information that you find in your dissertation research will come from articles, books, web-sties, news articles, reference books, etc. If you do not spend time recording this information while you perform your dissertation research, it will be nearly impossible to go back and retrace every single step of your dissertation research. And because you must present the findings of your dissertation research in the literature review, it is imperative that you keep carefully track of all that you read, study, learn and discover. Thus, with proper documentation and note-keeping as you do your dissertation research, you will be able to accurately and precisely document every aspect of your dissertation research and you will be able to detail this in your literature review.

The actual finding and gathering of information for your dissertation research is quite time consuming. This is because your dissertation research must be extremely extensive. Because the dissertation research is so time consuming, there are methodologies for dissertation research that have been developed in order to expedite the process of the dissertation research. In other words, there are specific guidelines and procedures to follow that can speed-up the lengthy process of the dissertation research. These guidelines and procedures will ensure that extensive dissertation research has been completed, and they will minimize the time spent doing so.

If you are struggling with the dissertation research aspect of your dissertation, there is help available. Dissertation consultants can help you expedite the process of dissertation research as dissertation consultants can take you through the step-by-step procedures and methodologies of performing dissertation research. Additionally, dissertation consultants can help you with your literature review. Thus, dissertation consultants can make the process of dissertation research both easy and relatively quick.

Dissertation Methodology

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Dissertation methodology is the methodology—or procedures and practices—that one must follow in order to write his or her dissertation. Additionally, the dissertation methodology of a dissertation is a chapter of the dissertation that describes all of the practices and procedures that the student has completed and followed while doing his or her dissertation.

The dissertation is the culmination of a student’s academic career, and it is a lengthy and difficult research project that must shed light on some new aspect on the field that the student studies. The dissertation relies on statistics for this, as statistics are used to prove whatever it is the student is researching. And because statistics is a science that must follow precise practices, rules, guidelines and procedures in order to gain accurate statistics, it is very important to document all of the procedures and practices that the student uses to achieve his or her results. This is where the dissertation methodology chapter of the dissertation comes in. The dissertation methodology chapter of the dissertation is where the student can document and detail every single step that he or she has taken during the long process of his or her dissertation. The dissertation methodology chapter allows other researchers to check and recheck all of the procedures, guidelines, practices (or methodologies) that the student has followed. Without the dissertation methodology chapter of the dissertation, other researchers would not be able to verify what has been completed. Therefore, the dissertation methodology chapter is extremely important because without the dissertation methodology chapter, a dissertation is not valid or accepted.

As explained above, a student must follow very precise guidelines, rules, regulations and practices in order to acquire accurate and precise statistics. Again, because these statistics will prove the student’s topic and point, it is essential that accurate statistics are obtained and used. Many students, however, do not know the ‘ins and outs’ of statistics as many students have not spent much time studying the laws of statistics. Thus, when it comes to the methodology of the dissertation and the dissertation methodology chapter, the student is at a loss in terms of knowing exactly what to do. The struggling student, then, wastes valuable time trying to figure out the dissertation methodology. Additionally, if the dissertation methodology is incorrect, the student looses additional time as the student will gather invalid statistics. It is therefore very important that the dissertation methodology chapter is done correctly.

Help is available for those students who struggle with statistics and who therefore struggle with the dissertation methodology. This help can come from an advisor, though many advisors are not always available to help with the dissertation methodology. Or, many advisors point out mistakes in the dissertation methodology chapter after a student has spent much time on the dissertation methodology. That time already spent on the dissertation methodology has been wasted, then, as the dissertation methodology has been done incorrectly. Instead of following a faulty dissertation methodology, a student can get valuable help on his or her dissertation methodology if he or she gets help from dissertation consultants. Dissertation consultants are trained experts in statistics and are therefore experts in dissertation methodology. Because these consultants know how to perform statistics and how to get accurate, precise and valid results, these consultants can help a student with the dissertation methodology. A dissertation consultant also knows the proper format for the dissertation methodology chapter, and a dissertation consultant can ensure that the entire dissertation is done correctly—including the dissertation methodology section.

Thus, there is no reason to spend time wondering how to acquire accurate statistics and how to navigate through the difficult dissertation methodology when help is so readily available. With the help of a dissertation consultant, the student will have an accurate dissertation methodology chapter and will therefore know exactly what needs to be done and how it needs to be done in order to achieve accurate and valid results.

Dissertation Consulting

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Dissertation consulting is the only way to go in terms of getting help on your dissertation. As you probably already know, the dissertation is a long, difficult and complex project that takes an immense amount of time. In fact, most people who are working on their dissertations would consider the dissertation the hardest thing that they have done in their academic life. This is because the dissertation is the last hurdle in obtaining a doctoral degree, and therefore the dissertation is the most difficult to complete.

Dissertation consulting can help, however, as dissertation consulting can make sure that a student completes his or her dissertation both on-time and with success. Dissertation consulting can help students at the onset of their projects and this help will be sustained throughout the entire dissertation. Thus, there is no reason for a student to struggle alone as dissertation consulting can make the entire process manageable and understandable.

The reason why dissertations can take so long is because there is much work to be completed for the dissertation. The dissertation must provide new information to the field, and this is by no means an easy task. Thus, careful research must be done in order for the dissertation to provide new information to the field. The student, then, must do extensive research to check to see if information already exists—if there are already studies or data on their particular topic. Dissertation consulting can help with that research. This help provided by dissertation consulting can expedite the process to an enormous degree. With dissertation consulting, the process of dissertation research is manageable and quick. Additionally, in the dissertation research, the student must document and keep track of everything that he or she finds. This too can be time consuming, but dissertation consulting can instruct the student in this manner and dissertation consulting can ensure that the student records all of the information properly. This information will be used later in the dissertation literature review—which also can be time consuming to complete. Here again, dissertation consulting can expedite the process of writing a literature review, because the people who provide dissertation consulting know the format of the literature review. The people who provide dissertation consulting also know how to accurately synthesize the information obtained in the dissertation research and therefore dissertation consulting will help students expedite the process of both the dissertation research and the dissertation literature review.

A common theme so far has been that dissertation consulting can expedite processes. Nothing is more true when it comes to gathering statistics that are necessary for the dissertation. Dissertation consulting can prove to be invaluable when it comes to the statistics portion of the dissertation. And because nothing is more important than the statistics of a dissertation, dissertation consulting is by far the best tool for the statistics portion of the student’s dissertation.

Dissertation consulting will make the process of the statistics easy, understandable and manageable. Additionally, dissertation consulting will provide a step-by-step guideline of how to gather, interpret and use statistics accurately and precisely. Each one of these steps (the gathering, the interpreting and the use of statistics) is extremely challenging and difficult – but dissertation consulting can break down these three steps into manageable feats. Thus, with dissertation consulting, the student can be well on his or her way to achieving success in statistics and therefore acquiring his or her degree.

There is no better way to ensure that a student finishes on time than by seeking dissertation consulting. There is no reason for a student to struggle through the difficult process of the dissertation when dissertation consulting is available at a reasonable price.

Correlation

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The bivariate measurement of strengths or association between two variables is called Correlation. It is a statistical technique that determines the status and way of relationship between two variables. Thus, correlation is the relationship of two apparently different aspects with some common connection. The recognition and measurement of that common denominator is what is known as the Correlation. For example, the relationship between poverty and illiteracy can be determined as the impact of one (poverty) over the increase or decrease in the intensity of the other (illiteracy).

There are many techniques of correlation. Pearson/product–moment correlation is the most commonly used technique. Sometimes when there is a requirement of determining the relationship between two variables, after removing the effect of one or more variables, the technique of partial correlation is used, which is an alternative type of Pearson/ product-moment correlation. All statistical techniques work with different types of data, and this is also true in the case of correlation. In other words, it is also applicable to quantifiable data. In quantifiable data, numbers are interpreted from quantities of different sorts through correlation. Correlation does not work on any sort of categorical data, like someone’s favorite color, favorite brand, gender, etc.

The end result of correlation is called the correlation coefficient. It is denoted by “r” and ranges from -1.0 to +1.0. This range of correlation means that the closer r is to +1 or -1, the more intensely the variables are linked. If r is near 0, then the correlation of the two variables tells us that they are not related at all. If r is closer to +1, then the correlation between them states that both of them are directly proportional to each other. In other words, it means that if one variable will expand, the other variable will also expand. In case the correlation between the two variables is -1, the two are inversely proportional to each other. In other words, the correlation means that if one variable expands, then the other will be lessened or become smaller. To make the value of the correlation coefficient easier to understand, the value of the correlation coefficient is squared. That square of the correlation coefficient is equal to the percentage with which the variation of one variable is related to the variation of the other variable. After the correlation coefficient r is squared, the decimal point in it can be ignored. For example, if the value of r is .3, then the square of it will be .9, which means that the correlation coefficient between the two variables is 9%(.3 squared and decimal ignored). If the value of the correlation coefficient is .4, it means that the correlation coefficient between the two variables is 16%(.4 squared and decimal ignored).

While using the correlation technique, we should also keep in mind that it only works on linear relationships and not on curvilinear (where the relationship does not follow a straight line) relationships. For example, in health and financial conditions, the variables are related but not linearly. Therefore, the data will not be quantifiable and therefore cannot be determined by the correlation technique.

Dissertation Statistics Consulting

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If you are stuck somewhere at the beginning, middle or end of your dissertation, dissertation statistics consulting is the best course of action for you. This is because dissertation statistics consulting can provide fast, easy, and accurate results for you as you complete the very difficult and very lengthy process of finishing your dissertation.

The dissertation is probably the hardest thing that you have done academically to date. This makes sense, however, as it is your last hurdle before you receive you doctoral degree. Thus, it is purposefully difficult and lengthy—as you must complete it in order to finish university with the prestigious title of “Doctor.” Dissertation statistics consulting can help you attain this prestigious title, as dissertation statistics consulting is designed to take you step-by-step through your dissertation.
Dissertation statistics consulting does exactly what its name suggests: it consults students as they aim to finish their dissertation. As such, dissertation statistics consulting can step into a project or dissertation at any stage. So, if you are just beginning your dissertation, dissertation statistics consulting can be extremely useful to you. Obviously, the sooner you acquire dissertation statistics consulting, the more help you can receive, and the easier it will be for you to complete your dissertation successfully. If you are half way through your dissertation and you are seeking help because you have perhaps taken a wrong turn somewhere, dissertation statistics consulting can also be a tremendous help. Dissertation statistics consulting will get you back on track and dissertation statistics consulting will make sure that you continue to travel in the right direction. This is extremely helpful because it can take someone months and months to figure out where he or she has gone wrong. This wasted time is not necessary with dissertation statistics consulting, however, as dissertation statistics consulting will spot the problem and help you correct it. Finally, if you are in the final stages of your dissertation, dissertation statistics consulting can also be of great help to you. This is true because dissertation statistics consulting can help you put the “finishing touches” on your dissertation. These “finishing touches” can actually slow a student down quite a bit, and dissertation statistics consulting can expedite the final processes of a dissertation. Thus, if you are close to finishing, dissertation statistics consulting will ensure that you finish quickly and successfully. Dissertation statistics consulting does this by checking every single aspect of your dissertation. In fact, dissertation statistics consulting will even edit your dissertation, so that you turn in a “clean” version of your dissertation—free of annoying typos and misspelled words. Thus, dissertation statistics consulting can help any student, regardless of where they are in the dissertation writing process.

Dissertation statistics consulting is most helpful on statistics. The statistics portion of the dissertation is by far the hardest and lengthiest aspect of the dissertation. Dissertation statistics consulting can change this, however, as dissertation statistics consulting can provide extremely precise information and help with statistical parts of a student’s dissertation. This includes providing hands-on help with the data collection part of statistics, the interpretation of that data and the incorporating of the interpretations into the dissertation. A mistake in the statistical part of the dissertation can derail the completion of a dissertation for months, if not years, and dissertation statistics consulting will make sure that a student does not fall into the many pitfalls involved in the statistical aspect of his or her dissertation.
Dissertation statistics consulting is the absolute best way to finish your dissertation. Thus, there is no reason for a student to struggle alone without the help of dissertation statistics consulting.

Independent and Dependent Variables

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Variables are defined as the properties or characteristics of some events that take on different values or amounts. There are basically two types of variables. They are as follows:

1. Independent variables
2. Dependent variables

Independent variables are those kinds of variables that are used for predicting the variation caused by the dependent variables in regression. Independent variables are also termed as predictors. Independent variables refer to the alternatives that are manipulated and are measured as well as compared. Independent variables are the type of variables that are not affected by any other variables, and are not changed by other variables abruptly. The concept of independent variables can be very well explained with the help of an example, like how the grades of a student can be affected by factors including how much time he devoted to studying, how many hours he slept, what his diet was, etc. These factors are independent variables as they are not at all affected by the grades of the students.

The second type of variable is the dependent variable. Like its name suggests, the dependent variables are always dependent on the independent variables. The variations caused by the dependent variables are generally explained by the independent variables in regression. The other name for dependent variables is predicted variables. The dependent variables are named the predicted variables because they are those types of variables that are predicted by the predictor variables or the independent variables. The other name for dependent variables is criterion variables. Considering the previous example, the score of the students, which are affected by several factors, is the dependent variable. Observing the relationship between the two things is used to find out what affects the dependent variable the most.

We shall now describe the dependent and the independent variables in the following cases:
For the case of the linear model, the general equation is described as the following:

So, in this model, the variable ‘Y’ is defined as the dependent variable, and the variable ‘X’ is defined as the independent variable.

In the regression model, the equation is given by the following:

The regressors called the βij (j=1, ,p) are defined as the independent variables, and the regressands Yi are defined as the dependent variables.

The independent variables are also called ‘ regressors’ and sometimes the independent variables are called the ‘control variables.’ This is because the independent variables are the ones that control the dependent variables. The other name for independent variables is ‘explanatory variables.’

Regression Analysis

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Regression analysis is a statistical technique that is widely used for research. Regression analysis is used to predict the behavior of the dependent variables, based on the set of independent variables. In regression analysis, dependent variables can be metric or non-metric and the independent variable can be metric, categorical, or both a combination of metric and categorical. These days, researchers are using regression analysis in two manners, for linear regression analysis and for non-linear regression analysis. Linear regression analysis is further divided into two types, simple linear regression analysis and multiple linear regression analysis. In simple linear regression analysis, there is a dependent variable and an independent variable. In multiple linear regressions analysis, there is a dependent variable and many independent variables. Non- linear regression analysis is also of two types, simple non-linear regression analysis and multiple non-linear regression analysis. When there is a non-liner relationship between the dependent and independent variables and there is a dependent and an independent variable, then it said to be simple non-liner regression analysis. When there is a dependent variable and two or more than two independent variables, then it said to be multiple non-linear regression.

There is a difference between linear and non-linear regression analysis. Linear regression analysis is based on assumptions. These assumptions are as follows:

1. There is normal distribution.
2. There is a linear relationship between the dependent and independent variable.
3. There is no multicollinearity between the independent variables or no exact correlation between the independent variable.
4. There is no autocorrelation.
5. The means lagged value of the regression variable does not affect the current value.
6. The homoscedasticity or variance between all the independent variables is equal.

However, in the non-linear regression analysis, there are no assumptions like autocorrelation, multicollinearity, homoscedasticity, etc. Non-linear regression is used when linear regression does not meet these assumptions. Logistic regression is an example of non-linear regression.

Most researchers use two methods to calculate the coefficient of the regression analysis. The first method is the OLS method, which stands for the ordinary least square method. The second method is the maximum likelihood method. The OLS method is used when there is a linear relationship between the dependent and independent variables. The maximum likelihood method can be used in non-linear relationships as well. When there is a non-linear relationship between the dependent and independent variables, most of the researchers transform the data in the linear form, and then they use the OLS method. The Maximum likelihood method is quite mathematical, and that is why many researchers prefer the OLS method in regression analysis. But these days, computers can solve this problem quite easily. Now the researchers are using the OLS and maximum likelihood method equally.

Regression analysis has two types of variables; one is the dependent and the other is the independent variable. The intercept term in regression analysis shows the common variance explained by all the independent variables, and the beta coefficient shows the rate of change. The Beta coefficient shows how the dependent variable alters when one unit of the independent variable increases. In regression analysis, R-square shows how much total variance is explained by the independent variable for the dependent variable. In regression analysis, the t-test is used to test the significance of the variable. In regression analysis, if the independent variable is categorical in nature, then the researcher must have to convert that independent variable into a dummy variable. For example, the male and female is converted into 0 and 1. When a dependent variable is categorical in nature, then a simple regression cannot be used. In such situations, logistic regression is used. When the dependent variable has two categories, then the binary logistic can be used to predict the probability of the dependent variable categories. But if the categories of the dependent variables are more than two, then multinomial logistic regression is used to predict the probability of the categories of the dependent variable. When dependent variable categories are ordinal in nature, then ordinal logistic regression is used to predict the probability of the dependent variable categories. In time series analysis, regression analysis is used very frequently. ARIMA, ARCH, VAR, and Co-integration are examples of regression analysis in time series analysis.

Survey Research

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The concept of survey research is defined as the research that focuses upon those surveys that are performed on the basis of advanced scientific knowledge.

Survey research basically provides knowledge about quantitative description of a few aspects of study.

The analysis that is carried out by the process of survey research is entirely concerned, either with the association between the variables, or with the findings of the project in a descriptive manner. The concept of survey research is that it is basically a kind of quantitative method that needs standardized kinds of information about the subjects under study. The subjects whom are being studied in survey research generally include individuals, groups, organizations or communities.

The second characteristic of survey research involves the extraction of knowledge by questioning structured and predefined questions by the people participating in the study. The responses that are given by the respondents in survey research consist of the data that is being analyzed.

The third characteristic of survey research is generally extracted by considering only a fraction of the study population. For example, this is done with service or manufacturing organizations, etc. Generally, the sample in survey research is quiet large and can allow the researcher to perform extensive statistical analyses.

The nature of survey research can be easily and comfortably understood by comparing two methods, namely case study methods and laboratory experiments.

Case studies in survey research refer to the examination of the phenomenon in its natural setting. In survey research, the researcher cannot control the occurrence of that particular phenomenon. But the researcher can definitely control the scope and the time of the examination. The researcher in survey research might or might not have already defined independent variables and dependent variables.

In case studies, which are important for the researcher in survey research, mainly involve the relationship between the context and the phenomenon of interest. In survey research, the researcher conducts the manipulation of the independent variables and then observes their corresponding effects on the dependent variables.

Laboratory experiments in survey research are the ones that are well matched with the research projects, and that involve comparatively limited and well defined strategies and propositions. These experiments in survey research involve few individuals, or a small group of people.

The researcher in survey research has direct control over laboratory conditions and manipulation of the independent variables.

The process of survey research is applicable when the researcher is primarily interested in knowing about the event, in knowing the reason behind the manner the event has occurred, and in knowing the reason behind the occurrence of an event. The process of survey research is quite useful in answering many types of questions. In fact, survey research is carried out to answer many types of questions.

The process of survey research is also applicable and useful in cases where the control of the independent and dependent variables is not possible and is not desirable. The process of survey research is also applicable in cases where the phenomenon of interest on which the survey research is carried out has occurred in the present time or in the recent past. The process of survey research is applicable in cases where the phenomenon of interest should be in its natural settings.

The inappropriateness of the survey research must also be kept in mind. Survey research is inappropriate in cases when detailed understanding of the context and history of the given computing phenomena is desired.

Statistical Power

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Data acquired and accumulated through research and observations can be inferred and interpreted with the help of statistics. Statistical analysis is the most reliable and dependable method of procuring the best and most accurate results on any given topic. This is where statistical power enters the arena.

Statistical power has established itself as a crucial element in the present day. To eliminate and deal with Type II errors that may prove to be menacing and potentially dangerous, (especially in pharmaceutical research) statistical power is crucial.

There are two types of errors that exist in statistical research, and they are type I and type II errors. Type I errors are those errors when a researcher rejects a true hypothesis as true, and type II errors are the exact opposite. To control the occurrence of type II errors, statistical power has been created. Statistical power was specifically designed to prevent null hypotheses from getting accepted as true. Since the offset of statistical power against type II errors, such errors have been controlled and prevented. Statistical power has been a very useful tool in researches and experiments.

Given the growing need for evidence-based practices in the world today, statistical power has done much in the world. Instead of accepting as true what is actually a null hypothesis, statistical power helps the researcher to identify the difference. Considering the dangers of taking a null hypothesis as true, statistical power acts as the probability (1-β) of rejecting null hypothesis when it is false. Statistical power ensures that the null hypothesis is rejected so it allows the researcher to avoid type II errors. Statistical power must be kept correspondingly high. The more the statistical power, the less the chance of having type II errors.

The analysis on Statistical Power is called Power Analysis. To analyze statistical power through power analysis, an analysis can be done both on data collected prior and post. Statistical power usually depends upon the desired power level and the desired level of significance in the test. Here, statistical power particularly identifies the level or possibility of preventing a type II error. On most occasions, the researcher takes the power level at 0.80, or 80% chance of not making the error. The level of significance signifies that a sample is probably about to get linked with the population. For instance, if the level of significance is 5%, then the sample drawn should have at least 5% characteristics of the population from where it has been drawn in statistical power. Statistical power is also decided by the strength of association or the effect size in the population. In statistical power, the effect size or the strength of association generally refers to the strength of association between the two variables. Hence, the greater the effect size, the more the statistical power. A greater effect size accentuates a greater Statistical power. The sensitivity of the data and the size of the sample also determine statistical power. In statistical power, sensitivity refers to the number of true positives out of the total of true positives and false negatives. In layman terminology, sensitivity relates only to data which is totally correct. This in turn implies that high sensitivity will give way to good data and finally a high statistical power. With high statistical power, there is access to data which has fewer type II errors.

The determination of the sample size of past data is very important in statistical power. This sample size keeps the significance of statistical power high, thereby denoting a larger sample size. With greater statistical power, errors (like type II errors) can be slowly prevented and controlled.

Methodology

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In statistics, methodology is a very important and useful tool. Given the mounting need of evidence-based practices in today’s world of challenging competition, statistics is very important.

Methodology in statistics forms the core foundation for various statistical tests and examinations.

In the field of psychology, where experimental testing is carried out, statistics is crucial. Psychology students conduct tests like personality tests (MMPI), IQ tests (Wechsler) and many different tests that require methodology and specific techniques. For execution of the methodology, questionnaires, surveys and tests are designed and conducted. A specific methodology is also utilized while determining the existence of certain pathological diseases or symptoms within the individual or a group of individuals. Questionnaires are very popular modes of methodology in statistics.

Psychology requires a certain mode, tactic, or methodology, by which the psychologist reaches his conclusion. Methodology in statistics is crucial as hypotheses and theories are drawn-out and validated with the help of the questionnaires or surveys. For instance, if an IQ test needed to be conducted between two schools – ‘A’ and ‘B’—, the psychologist can do that with the use of a methodology. The psychologist first prepares the questionnaires in which questions relating to general awareness are asked. Then he/she distributes it to the students. Through the results, with the help of methodology, the answers to questions may be attained. Methodology is crucial in psychology as it charts the line of action for the statistician so that he/she may attain a comprehensive and clear conclusion.

In science and medicine, methodology plays a significant role. For conducting medical research like bio-statistics, clinical trials, survival analysis, tests of hypothesis in statistical inference, etc., methodology is required. With methodology, public health and problems are analyzed. This includes studying bio-statistics, ensuring safety of data through clinical trials, and attaining knowledge of the population at any given time through survival analysis. In survival analysis, methodology determines the population that may have existed at a certain time in the past. Mathematically, this methodology can be observed as the likelihood of a persons death at time ‘T,’ which would be much later than time ‘t.’ As age increase, this methodology is presupposed to touch zero. In determining medical errors and risks of improper and uncalculated dosages of a particular drug, the test of hypothesis is conducted. This methodology helps in removing type II errors, which may occur with improper dosage of drugs.

Methodology should be strictly adhered to by the practitioner or nurse. Methodology allows researchers to utilize software like SAS for analyzing the data. For achieving accurate and precise results, methodology is binding on the researchers. There is a specific methodology for each of the tests and each of these tests achieves specific objectives.

Business is another such field where methodology is highly valued. Financial analysis, marketing researches, econometrics, auditing and production (and operations including services improvement), all require methodology and statistics. Methodology in the lines of commerce and business involves financial modeling. The financial modeling methodology is usually carried out by the financial analysts who write reports and provide information illustrating the company’s prospects. With a certain methodology, financial analysts develop certain models like Discounted Cash Flow model, binomial prizing model, etc. that help analyze the annual report. Technical analysts follow the time series modeling methodology to predict forecasts and price values of commodities. Through this methodology, they also analyze and predict the Sensex. Econometrics methodology is another instrument of statistics in business. It is a mixture of both economics and mathematical statistics and the methodology that it abides by involves statistical models like regression, binomial prizing model, etc.

In such technical fields, methodology is of the essence. In today’s world where evidence-based practices are required, methodology is necessary in most fields— particularly those fields where facts and figures are needed.