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Stratified sampling: An effective approach for dividing the population into subgroups

Stratified sampling: An effective approach for dividing the population into subgroups

In research design, the practical formulation is essential and hence must be done with immense care. But during the formulation of study on practical grounds, a large number of problems pertaining to determining the characteristics of the whole population or the part of the population creeps in accidentally. To encounter such problems, a technique known as sampling is employed in research.

Simply put, the sampling technique is a process of drawing a definite number of observations or individuals from the total population under investigation. Sampling methods are of various types, for example, snowball sampling, random sampling, etc. which can be used for different purposes. However, if the individuals in the population need to be defined using specific criteria, then we generally rely on the stratified sampling approach.

Stratified sampling involves the segregation of population into smaller subsets known as strata. In this type of sampling method, the strata are formed based on the characteristics or attributes of the individuals. Stratified sampling is widely used under the following circumstances.

  • Specific subgroups within the population of interest need to be highlighted
  • The target population is significantly heterogeneous
  • A relationship between two or more subgroups need to be determined
  • Representative samples from inaccessible subgroups must be created

Stratified sampling requires higher statistical precision when compared to any other form of sampling method. This is because the variability within the subgroups is lesser the variations of the whole population. 

Stratified sampling is of two types.

1. Proportionate stratified sampling – In this type of sampling method, each stratum sample size is directly proportional to the population size of the whole population of strata. This means that each strata sampling includes similar sampling factor. The proportionate stratified sampling is represented by an equation,

nh = ( Nh / N ) * n, 

Where,

nh is the sample size of ‘hth stratum

Nh is the population size of ‘hth stratum

N is the size of whole population

n is the size of entire sample

For example. If you have 3 strata and the sampling fraction is ½, then the final sampling sizes are as given in the table.

Sampling ABC
Population size200300400
Sampling fraction1/21/21/2
Final sampling size 100150200

Here, irrespective of sampling size the sampling fraction will remain the same.


2. Disproportionate stratified sampling – Typically, the sampling fraction is a differentiating factor between proportionate and disproportionate stratified sampling. Unlike the proportionate method, this type of sampling approach has different sampling fraction. 

Consider an example where you have three sample sizes and different sampling fraction. Then the final sampling size is as follows.

Sample ABC
Population size2005001000
Sampling fraction1/41/21/4
Final sampling size 50250250

In this type of sampling, if the fractions alloted are not precise, then the results may be biased due to under or over presented data. 

Stratified sampling technique works best when the population is a finite number, includes subgroups and the strata within the population is non-overlapping. 

The steps included in this sampling technique are:

a) Describe target audience – The first step in the define the target audience and decide the sample size.

b) Recognize stratification variables – This is followed by recognizing the stratification variables and determine the number of strata to be utilized. The stratification variables must align with the major objective of the research. If there is any additional information in the study, then such information to plays a role in determining the stratification variable. 

For example, if the objective of the study is to understand the subgroups, then the variables will relate to the subgroups and the information pertaining to the subgroups will influence the variables. Ideally, a study should include only a maximum of 6 strata and 4-6 stratification variables. 

c) Develop sampling frame – Next, create a new frame or use existing sampling frame that includes all the necessary information of the stratification variable for the elements in the target audience.

d) Evaluate the sampling frame – Assess the sampling frame on the basis of grouping, overlapping and make the required changes.

e) Assign unique numbers to element of strata – Ensure that each stratum is unique, and the difference between the two strata is different from each other. Then, assign a unique and random number to each element.

f) Identify the strata size – Determine the study requirements and figure the size of the stratum. The numerical distribution will identify the type of sampling. Next, choose random samples and form the required sample. 

Note: every element in the population must fit into one stratum. Put other words, an individual cannot be in more than 1 group. 

Today, stratified sampling is popular among the research scholars because of the number of benefits such as improved accuracy, exactness nature of sampling technique, and ability its to cover the maximum population. 

Quasi-Experimental Design: A Sneak Peek to Research Technique that Tests a Causal Hypothesis

Quasi-Experimental Design: A Sneak Peek to Research Technique that Tests a Causal Hypothesis

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

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

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

Types of quasi-experimental research designs 

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

  • Non-equivalent group, posttest only design – This type of research design includes administration of outcomes measures to treatment group or two groups and a comparison. For instance,  a group of students might receive coding instruction using the latest programming language whereas another group of students might receive writing instruction using standard programming language. After a week, a writing comprehension test is administered to determine which programming language is more effective. However, the major setback of this design is that the two selected groups may differ in important ways that impact the writing process. For example, if a group of students who code using standard programming language, then we cannot determine if the students are well-prepared or if it’s the result of utilization of standard programming language.
  • Non-equivalent control group design – Here we compare the control group and the experimental group. The groups are selected & assigned through convenience rather than choosing via randomization. But the problem arises when the results of the control and experimental group are to be compared. For instance, a researcher wants to determine the impact of online training on the average grade point of class 11 students. Here the researcher cannot randomly collect the participants as the institution will not permit to regroup the classes. Therefore, the researcher chose two sections of class11 from the same institution. Since the participants were not randomly allocated, the researcher cannot conclude that two groups were equivalent before the manipulation. Also, it cannot be determined if the difference in the grade point is only due to the impact of online training as other variables such as intelligence, motivation, etc. can bring about the difference in learning.
  • Separate pretest-posttest sample design – The main idea of this research design is that the individual selected for the pretest is not the same as that of the posttest. For example, assume that the two companies are similar. You can use one company to implement your study and second company as a control. A customer satisfaction program is developed. Initially, the customer satisfaction is measured without implementing the program. This is followed by the implementation of program and measuring the client satisfaction. Here the clients for each company will be different for pretest and posttest. The response of the client from the pretest and posttest cannot be compared. As a result, nonequivalence exists not just between companies but also between the pre and post groups.
  •  Double pretest design – This type of quasi-experimental research design is regarded as the strongest design with respect to internal validity. This is because, in the pre-post nonequivalent research design, the nonequivalent groups may differ from one another. Pretest does not tell us if the changing at the same rates prior to the program. But with a double pretest design, we can determine the rate of change through pretest1 and pretest2. Therefore, this research is explicitly used to control the selection of maturation threat. 
  • Repeated treatment design – Here the treatment is withdrawn and then presented for the second time. Simply said, treatment is presented more than once. The response of the participant is measured prior to and after the implementation of treatment. The treatment program is withdrawn and then the process is performed again. Consider an example where the government has banned the consumption of alcohol. To analyze the impact of this policy, problems pertaining to alcohol consumption were assessed. The outcome of the policy was the health of individuals improved as a result of the ban. 

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

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

Proven Tips to Develop a well-designed Questionnaire for Social Science Research

Proven Tips to Develop a well-designed Questionnaire for Social Science Research

Social science research is regarded as the primary tool to illustrate and predict the human behaviour. The outcomes of research contribute to the advancement in the academics and policy making. The results are based on the data collected via questioning the respondents (survey process). 

The most crucial part of the survey process is the creation of questionnaire. Inconsistent questions generate ambiguous & incoherent outcome of the research. Therefore, it becomes a necessity to develop an appropriate and organised questionnaire that measures the opinion & behaviour of the public. 

Depending on the needs, questionnaire is segregated into structured, unstructured and combination of these two studies is the quasi-structured questionnaire. 

  • Structured questionnaire includes well-defined pre-coded questions. This can be used to collect quantitative data. 
  • Unstructured questionnaire includes open-ended, vague opinion-type questions and is commonly used in focus discussions. 
  • Having a structured questionnaire with a few unstructured questions whose answers are not feasible is known as quasi-structured questionnaire. This type of questionnaire is most commonly used in social science research. 

Questionnaire design is a multistage process requiring an eye for details. It is considered as one of the most complicated tasks because surveys demand topics in varying degrees of detail. 

Best practices involved in designing a questionnaire 

Conducting pilot tests or focus groups in the initial stages of questionnaire development gives a clear idea of what people about the particular issue you are aiming to study. 

Step1 –  Identify the main goal of your questionnaire. Decide the nature of information(s) you want to collect. Formulate a research question that lies on the focal point of the questionnaire. This is followed by developing a hypothesis that is to be tested. The questions in the questionnaire must test the hypothesis which may be rejected or accepted on the basis of data analysis results.

Step 2 –  The next step is to choose the questions. Depending on the information gathered in the previous step, several possible types of questions can be included in the questionnaire. 

Some of them are:

  • Dichotomous question –  This type of question is generally of the form “yes/no” question, or “agree/disagree.” it is highly sensitive and simplest questions to analyse. 
  • Open-ended question –  This type of question allows the respondent to answer the questions in their own words and is commonly used to address the issue of “why.” The advantage of this kind of questions it that it provides insight into the feelings of the respondent. 
  • Multiple choice question – Mcqs enable easy analysis of results and consists of three or more categories of questions and demand a single answer.
  • Rank-order (or ordinal) scale question – Here the respondents are asked to choose or rank items in a particular order from a set. For instance, you can ask the respondent to order 5 things from most to least important. 
  • Rating scale question – A scale provides an equal number of negative & positive choices such as “strongly agree” or “strongly disagree.” Rating scale questions let the respondent to analyse the specific issue on the basis of a given dimension. 

Step 3 – This is the most important stage in the creation of questionnaire. That is the development of questions. The questions developed must be concise, clear,  brief and direct. Avoid using technical jargons (until and unless necessary), and complex statements as they may confuse the respondents leading to incorrect responses. Also, avoid asking biased questions and determine if you want to include options such as “not applicable for me.” The most crucial aspect is take immense care while asking for sensitive or personal information. Include them only if they are absolutely necessary. 

Step 4 – Development of questions is followed by sequence and skipping. The questions must begin with general and simple ones and then narrow down to specific ones. To build a sense of trust, rapport with your respondents, include common and non-controversial questions in the beginning of the questionnaire.

Step 5 – Once the questions are ready, pen down the questionnaire. This process includes two steps.

  • Details about interrogator (the one who asks questions) – Here, you must clarify if you are working as part of a team or as an individual. Include the name of your institution or University. For instance :”My name is Kiran and I am the only creator of this questionnaire. I belong to XYZ school of research.” 
  • Explain the purpose of your questionnaire –  Answering the questionnaire without understanding its purpose is next to impossible task. Many respondents might end up not answering the questions or provide misleading answers. Therefore, provide a brief explanation of your study or the purpose of the questionnaire and help them understand the underlying objective. 

Step 6 –  Prior to collecting information from the respondents, ask your peers to answers the questions and ask if your questionnaire requires modification or improvement and if the questions are clear enough. 

Master the art of developing a questionnaire, reduce errors and gather the required data for your study. 

Shape Your Thesis: Writing Up The Method Section For Qualitative Studies

Shape Your Thesis: Writing Up The Method Section For Qualitative Studies

As opposed to that of quantitative research, qualitative research focuses on the factors rather than describing the numerical data. There is no single qualitative method, rather a number of research methods fall under the roof of qualitative methods. The various domains, especially social science disciplines often tend to have different conventions on the best practice in qualitative research.

No matter which domain your research belong to, the research paper will definitely consist of a method section specifying, an appropriate sample recruitment strategy, sample size, and also an analytical strategy. As per the expert thesis proposal writers, qualitative research includes non-probability sampling. The unit of research may incorporate one or a combination of events, people, samples of natural behaviour, conversations, written or visual material, and many more. This section is basically called as ‘principle of selection.’ In this section:

  • The selection of these (events, people, etc) must be theoretically justified. For example, it must be made clear how the respondent was selected.
  • There must be a rationale for the sources of the data. For example, participants, settings, documents etc.
  • Consideration must be given to whether the sources of data (e.g people, events, organisations, documents) were unusual in some vital way.
  • Limitations of the data should be discussed. For example, the reason for non-response etc.

Basically, a qualitative research paper includes: data collection and data analysis section. In the data collection section describe the methods you have used to collect data for your research paper. Such as  survey method, observational or case studies approach. Include specific information pertaining to how many participants were present, the demographic information for each of the participants and how the information was verified.

Tip: According to the research consultants offering PhD thesis proposal writing service, some of the popular data collection methods are:

  1. Interviews – Interviews can be further divided into individual & focus groups.
  2. Participant observation – This process ranges from mostly observing to participating.
  3. Open-ended survey – This process gives an opportunity for participants to give detailed answers.

Data collection section should be followed by the data analysis section. The process of analysis should be made as crystal clear and transparent to help the readers gain clarity of the procedure you have followed. Describe the process of compilation of data, their organisation and how the conclusion was drawn.And also, how were the themes/concepts and categories generated from the data.  For example, if you have organised focus group interview, mention how you have organised the interview, compiled the obtained data, and how you have organised the obtained answers.

Now that you have learnt how to write a method section in a qualitative research paper, get your sleeves folded and get going. If need any assistance with the writing process, consult a team of writers offering affordable PhD thesis proposal writing service.

Guidelines to Abide for Effective Thesis Synopsis Writing

Guidelines to Abide for Effective Thesis Synopsis Writing

Undoubtedly, a synopsis form an integral part of a thesis that defines the future course of actions taken for research. It ensures that the review committee gets a clear picture of the proposed research and spots the gap established.

Writing a synopsis must be given due time, thought and necessary attention to specifications required. While writing your thesis synopsis, ensure the following:  

    1. It offers a comprehensive overview of  research areas which have been investigated
    1. It helps in verbalizing the idea of the thesis.
  1. It helps you to focus and structure the thesis.

A thesis synopsis should be brief but precise. Adopt these tried and tested guidelines to deliver a structured thesis synopsis:  

Introduction:

This section states the core research questions and all the important background facts throughout the procedure. It must clearly state the purpose of the study.

Title:

The title reflects the objective of the research. The title of the synopsis and title of the thesis shall be invariably the same. The title must include a creative or unique element and should not be either too long nor too short.

Aims and objectives:

Research consists of objectives and aims pertaining to the study problem. Usages of terms like “the first study”, “the only study”, etc. should be avoided.

Hypothesis:

The problem being studied should be mentioned in precise and clear terms. The hypothesis can be formulated by understanding the problem, reviewing the literature on it, and considering other factors.

Literature review:

A review of the relevant literature is another very important part of the synopsis. It shows the work done previously in the area of proposed research and assists in identifying various variables in the research project and conceptualizes their relationship.

Research methodology:

In synopsis, the research methodology describes a method which may be intended for use in the research. The methodology should cover the following aspects:

    • Sources of data (Primary or Secondary)
    • The survey, questionnaires, observation, case studies, portfolios, books, journals, periodicals, abstracts, indexes, directories, research reports, conference papers, online databases, the Internet, videos & broadcasts.  
    • Sample size
    • Data Collection Techniques
  • Analysis of Data

Results:

Briefly mention the key findings of your study

Conclusion:

This section includes the inference obtained, significant contributions of the research and shortcomings of the research.

Reference and bibliography:

In the end, a synopsis contains a list of references and a bibliography written in a standard pattern. Each and every aspect such as the name of the author, publication year, title, the title of journal/series, page number needs to be included.

The format for writing a synopsis varies from University to University and among disciplines. Above is the outline of how the thesis synopsis should look like. The synopsis is an important part of the thesis that cannot be taken lightly. It contains crucial chapters like literature review, research methodology, reference lists, with each having its own significance.

What is the best thesis writing advice for scholars?

What is the best thesis writing advice for scholars?

There is a glut of writing advice that is available for scholars, particularly that is related to thesis writing. The internet is flooded with books, blogs and articles that are getting circulated with writing advice and tips to allow them to handle the writing task easily. However, most of the available advice is repetitive and does not come of much help to the writer.

Some of the most common tips you would find available for your phd thesis writing:
1. You must write every day, right from the beginning of your PhD
2. Do not overthink while writing as this may come in the flow of your writing
3. Believe in doing work rather than doing perfect work, as improvisations can be done at a later stage
4. Take rewriting as an integral part of writing and not as a separate pressure or load.

You must surely not be oblivious to these tips being a PhD scholar but despite that all scholars, sometime or the other time, do encounter stressed phases in the process of thesis writing. The tips above are common and applicable to all but may not be effective for all, every time.

Writing is not a straight path. It is a process involving a lot of complexity and narrowing the thoughts down to a single statement advice is actual oversimplification of the complexity of the ordeal of writing.

Just trying to follow these tips blindly, I think would not work for the main reason that before following advice, you need to incorporate the skill for being able to apply these tips in a customised manner that could benefit you.You need to leave the simplification of the advice and the subtlety behind to be able to make it useful for you.

You would surely be reading advice from many corners and would come across theoretical models that claim to bring skill development, end of they though, it is your expertise that will determine the amount of efforts taken by you. As an amateur, a lot of concentration is wanted in all aspects related to writing but to a seasoned writer, the flow of writing comes more as a spontaneous action rather than a conscious effort.

Practice as a means to perfection isn’t just applicable to sports coaching but the flow is equally well in creative activities too because to come in the flow of doing things effortlessly, you must have high level of expertise. However, you being good at something doesn’t necessarily makes you a good advisor too. It is ultimately the writer who has to polish and surface out those skills to be able to adopt and adhere to the tips given by the advisors.

Writing a PhD Thesis Every Guide Wants to Read

Writing a PhD Thesis Every Guide Wants to Read

Most PhD students spend years of hard work in preparing and researching for their selected PhD project. Most of them also fall short when it comes to presenting the project thesis that can convey the depth of their research and their individual contribution to the solution of the original problem.

In addition to its details, the PhD thesis must be able to state the problem with clarity, review the existing solutions to the problem, provide a critical analysis of the same, and finally detail the proposed solution to the problem.

PhD Thesis

Listed below are some tips on writing the ideal PhD thesis that every guide would want to read and publish:

 

  • Structuring the thesis

Your thesis must have a structure and flow similar to any research paper. Although the exact structure can vary depending on your subject, the outline structure of your thesis can include an introduction, related work, experiments, and conclusions.

  • Is your thesis publishable?

A publishable thesis can be the delight of any guide. To achieve this, you will need to plan for this from the time of subject selection. Question yourself if your conducted experiments are extensive to survive any independent scientific scrutiny, or if the data used for the research is valid.

  • The importance of headings

As an alternative to generic headlines in your thesis, provide headings that provide a glimpse of what your content can be. Regarding use of sub-headings, use appropriate section numbering and do not exceed more than 3 levels.

  • The title of your thesis

In addition to the use of headings, the title of your thesis is vital to convey the extent of your research. Avoid using very short titles (for example, “Music Information Retrieval”), which sounds generic and does not convey much information of your research. Use appropriately long titles that indicate the scope of your research work.

  • Taking help from professionals

When it comes to effective writing, it is best to take the help of academic writing professionals who have the relevant skills and experience in preparing a complete thesis. An academic writer will be able to convey the depth of your research clearly using text and formatting.

  • Preparing for the viva

Review the quality of your thesis, which is likely to be examined by the panel of experts in the viva discussion. These experts will examine your thesis to check for completeness and overall quality, and to determine if presented data and analysis support the final conclusion.

Emerging Research Areas in Energy Economics

Emerging Research Areas in Energy Economics

Emerging Research Areas in Energy EconomicsIf the areas in the domain of applied economics are being looked at, then it can be experienced that out of all the areas, energy economics is the area, which is the most coveted of them all, owing to its multidisciplinary nature. The importance of this area lies in its scope, as this area focuses on the aspects of economic growth and development, linked with the problems regarding natural resources and energy pricing. Given its multidisciplinary nature and mounting amount of importance in the word of business and society, several research areas are emerging out of this particular domain of applied economics.

Within the scope of energy economics, there are several research areas, which are gradually turning out to be popular and significant among the researchers across the world. Signal ProcessingYou can also take help of scholarly writers to choose a good topic to begin your research study. Some of those areas are as per the following:

  • Rebound analysis: With the growth in industrialization across nations, demand of energy is on the rise, and due to several factors, usage of energy is not able to attain its optimum level. The association between expected usage of energy and the actual usage of energy is being tested by researchers by means of rebound analysis. This area is gradually turning out to be popular since last two to three years.
  • Efficiency analysis: Apart from the rebound analysis, efficiency analysis of energy generated from various sources are carried out based on several parameters, like energy price, energy demand, energy supply, number of transmission channels etc.
  • Environmental analysis: During the course of energy generation and consumption, several types of fossil fuels are used, and as a consequence of that, several kinds of environmental degradations, in terms of air, water, soil pollution etc. take place. Analysis of environmental impacts of the energy generation and consumption processes is gradually gaining importance among researchers.

For more information about the emerging and popular research areas in energy economics, kindly browse through the pages of www.phdthesiswriters.com.

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