Research Methods: Design Implementation and Analysis

Posted: January 5th, 2023

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Research Methods: Design Implementation and Analysis

Question 1

Qualitative researchers should strive to achieve the quality and trustworthiness of qualitative research to realize satisfying outcome. Often, a qualitative is carried out within various paradigms, or ways of acknowledging the nature of knowledge and reality, each related to various forms of describing, comprehending, and reporting the nature of quality (Ferero et al.). Trustworthiness in research, on the other hand, refers to the assurance that can be invested in the research outcomes. Trustworthiness relates to confirmability, which is the extent to which the findings of a research can be verified by other scholars (Ferero et al.). Trustworthiness in research could also refer as the extent to which the researcher’s findings are believable. Thus, a researcher out to play active roles in designing, performing, and reporting the study to make the outcomes credible. Thus, the primary objective of trustworthiness in qualitative research is to back up the argument that the study’s findings deserve adequate attention. Ferero et al. assert that this is particularly essential when utilising inductive content assessment as divisions are formed from the raw set of data without employing a theory-based classification model. A qualitative research that seeks to achieve trustworthiness should depict four primary features such as congruity, integrity, constancy, and reliability. Nevertheless, the question is how to achieve quality and trustworthiness when conducting a qualitative study. Overall, a researcher could achieve quality and trustworthiness by striving to present data that are trustworthy, formed through approaches such as building meaningful relationships with the research participants so that they do not find any challenge sharing valuable data (Ferero et al.). Furthermore, it is possible to determine the quality and trustworthiness of a research by looking at the consistency or confirmability of the decisions made during the process. Nevertheless, an essential factor to consider is the fact that achieving quality and trustworthiness of qualitative research requires researchers to consider different criteria as they would do when performing a quantitative study (Ferero et al.). Often, qualitative researchers consider four factors (credibility, transferability, dependability, and confirmability) when determining the quality and trustworthiness of their research. Following the four guidelines is critical because they offer a chance to create a study that is acceptable all over the globe in terms of quality and trustworthiness.

Credibility

Credibility is one of the criteria for examining the quality and trustworthiness of a qualitative research. Credibility implies that the research outcomes are trustworthy and reliable. A qualitative researcher can recognize credibility within the research by identifying an alignment between the theories, study questions, gathering data, data analysis, and the outcomes (Stenfors, Kajamaa, and Bennett 597). Furthermore, qualitative researchers term the process as being credible when the sampling technique, amount, and volume of data, and analytical measures are considered, and are suitable within the adopted framework (Stenfors, Kajamaa, and Bennett 597). Credibility of the study holds that the methodology used should be adequately justified and explicated. For instance, researchers may choose to utilise a phenomenological strategy or any other theory and use supportive data to support why they took a particular decision. Moreover, it is essential to justify the volume of data and data collection approaches. Depending on the study questions, observations and other techniques might be an alternative choice to conducting interviews, or engaging individuals in interviews may be more suitable than focus groups or interviews that engage many respondents (Stenfors, Kajamaa, and Bennett 598). The credibility of the analysis process in some qualitative researches can be improved via member reflection, which implies that the preliminary outcomes are presented before the participants for further explanation. Similarly, terms such as data adequacy or saturations are utilized to show credibility, indicating that adequate data were collected to identify all applicable features to respond to the research questions. The aspect is widely contended, nevertheless, and Stenfors, Kajamaa, and Bennett (598) give a substantial elaboration of why the power for information may be a more appropriate idea. They assert that researchers should be describe how the collected data are appropriate in terms of permitting for transferability, having the capacity to respond to the research question and being in line with their methodological approach.

Transferability

Transferability is another concept that helps qualitative researchers to determine the quality and trustworthiness of their research. Transferability means that the results of the research may be shifted to another group, context, or settings. Kitto, Chesters, and Grbich (243) argue that the transferability implies to the measure to which the outcomes of a study can be used or applied past the scope or bounds of the research. Kitto, Chesters, and Grbich (243) inform that transferability suggests that the outcomes of the research can be used or transferred to similar persons or situations. Researchers establish transferability by offering the audience or readers with adequate proof that the findings of the research could be applied to other populations and situations. A researcher recognizes transferability by considering the detailed descriptions of the setting or context in which the study was conducted, and how this influenced the outcomes. From a qualitative view, transferability is chiefly the function of the person conducting the generalization (Kitto, Chesters, and Grbich 244). Qualitative researchers can improve transferability by performing a thorough function of describing the context of the study and the primary assumptions in the whole process (Kitto, Chesters, and Grbich 244). The one in charge of transferring the outcomes to different conditions and contexts is in charge for determining the appropriateness of the transferability. It is imperative to acknowledge that as a researcher one cannot verify that the study outcomes will be appropriate or applicable. Instead, the role of a researcher is to give proof that it could be applied to other contexts. This may appear confusing but Kitto, Chesters, and Grbich (245) simplify it in their article by stating that it is not the role of the researcher to give a measure of transferability, instead, it is his or her obligation to give the data base that forms the basis of transferability applicable on the side of the relevant parties. Contrary to generalizability, transferability does not entail generalized claims, but asks readers or a qualitative research to find the relationship between the elements of a research and their own encounters. Thus, researchers of a qualitative process should pay considerable attention to transferability as a possible option for determining the quality and trustworthiness of their studies.

Dependability

Both researchers and readers can rely on dependability as an appropriate criteria for determining the quality and trustworthiness of the research. Dependability refers to the length or magnitude to which the study could be imitated in similar situations or conditions (Shengton 71). Shengton (71) further describes dependability as the reliability and consistency of the study results and the measure to which research processes are documented, permitting someone outside the study to monitor, appraise, and evaluate the study. Shengton (71) proceeds to mention that dependability is essential in determining trustworthiness because it forms the findings of the research as being repeatable and consistent. Those in charge of a research seek to affirm that their outcomes are in accordance with the collected data (Shengton 71). Researchers want to be certain that if other examiners and researchers appraise the data, they would reach at a similar conclusion and verifications, and assertions about the set of data. This is imperative to ensure that that nothing was skipped in the research process, or that the one responsible for the study was not misled or misguided in drafting the final results. While there are various techniques a researcher could to build dependability, one of the most suitable techniques to have an external researcher perform an inquiry review on the study (Shengton 71). The evaluation also called an external audit entails hiring a professional to assess key practices such as gathering of data, analysis process, and presentation of results. The audit happens to verify the preciseness of the results and to verify the outcomes are backed by the collected data. Furthermore, the external audit examine the interpretations, recommendations, and conclusion to verify that they have adequate support from data (Shengton 71). External audit are essential because they permit an outside researcher to evaluate, explore, and critic how the analysis and interpretation of data happened. Researchers can get helpful tips from the audit that may help to determine the quality and trustworthiness of the qualitative study (Shengton 71). The audience can recognize dependability in a qualitative research when there is adequate information offered such that other researchers could adhere to similar procedural measures, though each researcher could be aiming at different objectives.

Confirmability

Confirmability is a reliable criteria that helps researchers to identify whether the process achieves the targeted quality and trustworthiness. Confirmability means there is a clear connection or attachment between the collected and presented data and the outcomes (Korstjens and Moser 120). It also refers to the measure to which the results of the research process are could be verified by other scholars or researchers. In other words, the criterion has to do with the amount of confidence that the research findings are based on the sample or participants’ views and descriptions and not the perception and views of the researcher (Korstjens and Moser 121). Confirmability affirms that the outcomes are influenced by respondents or participants than they are influenced by the one steering the qualitative process. Confirmability is focused with affirming that the data and interpretations of the results are not only an imagination of the researcher, but evidently retrieved from data (Korstjens and Moser 121). One identifies confirmability in a research when the researcher vividly elaborates how they reached the conclusion through adequate descriptions.

Korstjens and Moser (123) identify two ways for establishing the confirmability of the research study’s outcomes; audit trial and reflexivity. Audit trial is the most common approach used to test confirmability because it is very helpful when formulating the results. An audit trail is when a qualitative researcher describes the process of data gathering, analysis, and deducing the data (Korstjens and Moser 123). A researcher uses the approach to document any unique or captivating during the process of gathering data, and put down their views about reaching a particular finding (Korstjens and Moser 123). Reflexivity, on the other hand, is the view or perception that a researcher embraces when gathering and analyising the collected data. A researcher in this scenario must assess their background and competence to assess how these impact on the research process.

Question 2

Although various groups, scholars, and institutions have diversified techniques to perform data analysis, the various approaches fit into one description. Data analysis according to Harding and Whitehead (142) refer to the act of refining, processing, and altering the collected raw data, and retrieving practical, relevant information that assists researchers make informed choices. Data analysis provides the chance to minimize the risks evident in decision-making by offering vital tips and statistical content, usually presented in graphs, charts, and tables. Evans-Winters, Edwards, and Esposito (39) on the other hand, refer to data analysis as a practice involving modeling and changing data to identify helpful information for research decision-making. The primary objective of data analysis is to acquire helpful information from data and making the decision depending collected data and the analysis process. Depending on the type of study and nature of data, researchers can choose from a wide range of data analysis strategies that could help to acquire refined information from a set of data (Harding and Whitehead 145). A possible approach is diagnostic analysis that allow analysts to learn the patterns in a set of data. Another possible technique is the predictive analysis, which answers the question “what is likely to occur”. Analysts using predictive analysis use patterns from past set of data as well as current trends to identify possible future happenings (Harding and Whitehead 149). While it may be impossible to come up with a completely precise prediction, the chances of making a precise forecast is higher when analysts have adequate information about the field to conduct intense research about it. Another approach that analysts use is the statistical data analysis technique that responds to the question “what transpired” (Harding and Whitehead 149). Statistical analysis touches on key research aspects such as data generation, analysis, interpretation, and presentation (Harding and Whitehead 150). Regardless of a data analysis method a researcher decides to use, he or she must adhere to the five critical steps that guide the process.

Step 1 – Organising the Data

Proper analysis is adequately guided data sets that are focused entirely on allowing viewing of the whole data in one aspect and are systematically organised to respond to the research questions beforehand. A suitable approach in this case is to refer to the interview, and recognise and distinguish between the various topics and topics the study is trying to answer, and those that were merely added in the interview framework as significant but not necessary at the moment (O’Connor and Gibson 66). Referring to the questions used in the interview offers an analyst a better chance to keep in mind what the study is trying to identify and why the researcher wanted to perform the interview in the initial place (O’Connor and Gibson 66). Once the questions are answered, it is essential to consider other themes and concepts that have developed from the data set. It is imperative to examine them in accordance with how they connect to the study questions and how they may be relevant in future.

Data organisation should happen in a way that is easy to examine, and that permit researchers to handle each topic to identify topics and concepts. One possible alternative to achieve this is to organise the data on the transcript, and formulate a chart. The chart should contain key elements such as the topics addressed in the research, the major features of the interview, and possible notes made from the interview (O’Connor and Gibson 67). An effective and graphical way of organising and presenting the data permits the researcher to examine the reactions to each topic and questions on individual basis, in order to simplify the process of picking relevant topics and concepts (O’Connor and Gibson 67). Once the data is organised properly, the analyst or researcher can transit to the next phase; identifying concepts and ideas and assigning them into distinct divisions.

Step 2 – Recognising and Categorising Concepts and Ideas

Recognising vital topic, recurring themes, trends of belief or views that connect setting and people is one of the most difficult aspect of data analysis that require much skills and competence because this phase plays significant functions in integrating the entire exercise. When examining the various reactions for a specific question, a researcher may focus on particular ideas, phrases, or words that keep recurring (O’Connor and Gibson 68). The researcher should document the various ideas as the reactions are read through. In addition to identifying the frequently used phrases and words, the researcher should consider knowing the meaning in language. O’Connor and Gibson (68) inform that it is sometimes possible to learn about a person’s feelings, views, and attitudes about something by simply recognising the words they utilise to express their thoughts. The participants most likely have a way for expressing their ideas. The way in which they make reference to certain things or incidences can represent their behaviours or attitudes. A researcher should identify and pick the expressions utilised regularly by respondents that may appear differently than how other participants would put their responses (O’Connor and Gibson 69). This is essential because the researcher ensures he or she comprehends what it depicted or represented by certain words of expressions and because it provides the chance to look up at the meaning and possible effects of the used expressions. A researcher should use this phase to identify unexpected reactions or occurrences that he or she did not expect to come across (O’Connor and Gibson 69). Besides, it is essential to spend time and examine the various stories presented by interviewees because some use such approaches to present or communicate their ideas quite effectively (O’Connor and Gibson 70). A fundamental step that follows the identification of expressions and their meanings is coding and categorising the concepts and ideas into groups or divisions that are easy to read and follow (O’Connor and Gibson 71). Successful coding and categorisation of concepts and ideas permit the researcher to proceed to the third phase of data analysis process.

Step 3 – Establishing Dominant Themes in the Data Set

Each of the categories having responses has at least one or more associated topics that offer a deeper insight into the data. The different sections can be placed under one dominant theme. However, it is only possible to identify the themes by familiarising with the data before assigning preliminary signs or codes to the data set with the motive of describing the content (O’Connor and Gibson 71). It is easier to identify the dominant themes by searching for patterns that help to review the content more appropriately. For example, in a research that seeks to find how a business will help TB patients regain stable health by providing relevant medication and education, a major theme that is likely to occur from an interview with the infected persons, and which may determine their eligibility for recruitment at the facility is isolation. The researcher or analyst in this case must consider how the condition relates to isolation with regard to the perception people have about the disease, and how isolation relates to the disease with it being highly infectious. Identifying a major them presents a suitable chance to pay considerable attention on the area, and develop proper guidance on the approach to take. Nevertheless, it could be difficult for the researcher to proceed effectively with the analysis without identifying the over-arching themes.

Step 4 – Checking Validity and Reliability in Data Analysis and Results

Prior to proceeding with the key activities under the category, it is helpful to be conversant with the meanings of validity and reliability as they relate to a qualitative research. O’Connor and Gibson (72) describe validity as the preciseness with which an approach measures what it is expected to measure, and produces data that actually depicts reality. Validation is not a distinct aspect of investigation, but rather an indispensable guide throughout the whole research practice. Reliability, on the other hand, refers to the consistency of the research outcomes. Promoting reliability need commitment and diligence on the researcher’s part, and requires one to have the capacity to transcribe and analyse the results (O’Connor and Gibson 72). A researcher or analyst in this should test hypothesis and findings because as patterns and themes emanate from the collected data, it is essential to assess the data, keenly identifying for adverse aspects of the trends or patterns (O’Connor and Gibson 73). In addition, the researcher should identify possible researcher effects bearing in mind that the aspects of interaction between the investigator and the respondent will be determined by the personal features of all participating sides. Moreover, variations in age, level of education, language, and background will all have substantial effects on the results of the interview. Another vital aspect at this phase is to confirm or validate the results especially through triangulation, which asserts that findings are largely dependable when they can be affirmed using more than a single approach and tool (O’Connor and Gibson 73). Another possible approach for validating the research outcomes is to acquire feedback from respondents. O’Connor and Gibson (74) assert that an effective manner to know the validity of research outcomes and of the data collector’s perception of them is for the one overseeing the practice to go back and ask participants or who can represent them. More fundamentally, a researcher at this phase should check for possible researcher effects because the aspects of the interaction between the data collector and the respondent will be impacted by the personal features of both sides.

Step 5 – Identifying Potential and Plausible Explanation of the Outcomes

The initial thing to do at this phase is to begin with summarising the dominant themes and results. The researcher may rely on certain questions to guide how they handle the process such as affirming whether the findings are what were anticipated based on the literature, and identify whether there were any emerging new issues in the results (O’Connor and Gibson 76). A researcher may also try to understand how the findings are the same or different to what is indicated in the literature from other studies of the same nature. A researcher at this phase may rely on various essential sources such as literature, personal notes, journal articles, observations, community collaborators, and other vital informants that are in a position to give the required information (O’Connor and Gibson 76). A researcher should remember to connect the outcomes to the context of ethnic or cultural experiences within each participant, especially when they come from different backgrounds (O’Connor and Gibson 76). This is not only essential in terms of identifying explanations of the outcomes, but also for knowing the effects for the study group.

Step 6 – Implications of Data Analysis Findings

After knowing the possible explanation for the findings, the researcher should consider their potential effects. A researcher at this case should consider why the work is essential, and why different groups should focus on its outcomes (O’Connor and Gibson 77). The researcher should go further to assess the effects of the findings on the community, as well as understand how various collaborating teams within the community respond to the outcomes (O’Connor and Gibson 77). The one in charge of the process should know that the results from the research should permit people not only in recognising techniques to bring about significant change, or to be more considerate to a society or community’s needs, but also assist in finding realistic approaches to executing the strategies.

Step 7 – Communicating or Presenting the Information

The researcher at this phase should begin by identifying the audience that will have reach to the information and it would impact on them. The one in charge of the process should focus on presenting the outcomes appropriately, adequately, and in collaboration with those impacted by the outcomes. It is imperative to understand that some of the study outcomes are sensitive and highly influential to some individuals and communities so it is important to know the best channel to present the results. Some of the possible avenues, include but not limited to newspapers, newsletters, mail, video, radio, formal reports, and seminars among others.

Step 8 – Organising the Information into a Refined Document/Report

This entails not only the research findings, but how the whole study process was conducted, what happened in accordance with plans, what deviated from the expectations, identifying the strengths and weaknesses as well as what the researcher would do differently and how it could be enhanced. One of the most vital factor to take into account when composing the final report of the data analysis is to be aware of the target audience.

Question 3

Question 3 A – Difference Between an Inductive and a Deductive Research Approach

A research can either be inductive or deductive. An inductive research is a systematic procedure for assessing the qualitative data in which the process is directed by particular evaluation goals. The inductive research approach is not appropriate where there is scarce or no topic because there will be no basis for testing a theory (Evans-Winters, Edwards and Esposito 84). The inductive process starts with making an observation, and then proceeding to observe a trend or pattern from the observation. The final process in an inductive research process is to establish a theory from the identified patterns (Evans-Winters, Edwards and Esposito 84). For example, an observation in a research could be that cows rely on water to survive, while an observed trend in this scenario could be that all monitored animals rely on water for their existence. The developed theory in this scenario is that all biological forms require water to be alive. The benefit of the inductive approach include, promoting flexibility, increased focus on a particular concept, and its continuous support for the production of new theories (Evans-Winters, Edwards and Esposito 84). The other merit for using the inductive approach is that it fosters further exploration as much as it starts with specific observations (Evans-Winters, Edwards and Esposito 84). Nevertheless, it is possible to get imprecise inferences due to the fact that the approach is quite limited. The other limitation with the approach is that the findings achieved from an inductive process can hardly be verified, but it is possible to invalidate them.

When performing a deductive research, on the other hand, a researcher often begins with a theory or the findings of an inductive process. A deductive approach implies testing or verifying the theories. Therefore, it is impossible to perform a deductive research in situations where theory lacks (Evans-Winters, Edwards and Esposito 86). Using the deductive research approach requires researcher to pay attention to four primary areas to achieve the most suitable outcomes. The first phase is to commence with an existing theory before creating a hypothesis following the available theory (Evans-Winters, Edwards and Esposito 86). A researcher should then gather the relevant data to support or refute the hypothesis. The final process is to analyse the outcomes, by determining whether the collected data support or contradict the hypothesis. A suitable example when conducting a deductive research is to begin with an existing theory that low cost carriers always experience delays, and to formulate a hypothesis based on available theory that if customers travel with a low cost carrier, then will encounter significant delays. The researcher should proceed to gather data about low cost airlines before reaching a conclusion that at least 4 out of 90 flights of low-cost carriers are not delayed, a result that does not support the hypothesis. The merits a researcher enjoys when using the deductive approach, include the ability to describe the connection between variables and concepts and the possibility of measuring relevant concepts using quantitative techniques (Evans-Winters, Edwards and Esposito 87). Furthermore, the approach presents a better chance to generalise the study results to a particular extent (Evans-Winters, Edwards and Esposito 87). Nevertheless, the approach is disadvantageous because the findings from the style can only be valid if all conditions set in the inductive research are appropriate and the terms are easy to follow (Evans-Winters, Edwards and Esposito 87). Thus, a researcher should be keen when selecting between inductive and deductive approach to achieve the targeted goals.  

It is essential to conduct some research first before selecting either the inductive or deductive reasoning approach to effectively apply either of the concepts in research. Conducting adequate research before proceeding with the selection provides a researcher with tangible information that helps to understand why one should choose one of the approaches over the other (Evans-Winters, Edwards and Esposito 91). The research, for example, helps to know whether a particular approach would suit a qualitative or quantitative research. Moreover, conducting a research prior to using either of the reasoning approaches present a better chance to be conversant with the possible merits and demerits associated with a particular style (Evans-Winters, Edwards and Esposito 91). Some of the suitable avenues for acquiring relevant information about the both reasoning approaches, and which may help one to settle on the most suitable style, include published materials such as books, journals, and other relevant forms. Researchers can also acquire the needed content from online sources such as individual and organizational websites. More fundamentally, researchers can share information and ideas with those who have already used either of the approaches to acquire necessary information.

Question 3 B – Article Analysis

Ziad El-Awad performs a research that uses a case-study approach with the objective of creating a process model that describes the learning procedures and mechanisms by which enterepreneural learning develops at multiple phases within the organisation. El-Awad (618) argues that using the transactive memory system model presents a chance to know how individual forms of knowledge and skills are routinised in non-human components, over a period of time, become entrenched in organisational procedures and guidelines. El-Awad (624) conducts a study that builds on eighteen semi-structured interviews and a series of observations. El-Awad’s study reveal that knowledge is transmitted from individuals to the firm through systems that function at the organisation-level, chiefly routinising behaviours and externalising various categories. The findings of the research are valuable because they give a dynamic perception of entrepreneurial learning underscoring the transactive and organisational aspects of transactive memory learning as being essential for instilling knowledge in business procedures and practices (El-Awad 628).

Mette Liljenberg and Daniel Nordholm, on the other hand, examines the organisational procedures introduced in learning institutions in a municipality in Sweden and look into the connection between performative and perceived components of improved working. The scholars consider their theoretical perception of retreat from entrepreneurial psychology and an OD view by fusing the coupling features of accommodation to past studies (Liljenberg and Nordholm 693). The analysis reveals that the performative and ostensive components of organisational practices must be adequately linked if advancement practices are to influence daily activities. Liljenberg and Nordholm (694) recommend that the situation to prevail, managers of advancement work should create and manage development initiatives that go past decoupling by also enhancing accommodation and integration. The results are essential because they offer a theoretical enrichment to knowing the association between performative and ostensive components of organisational procedures, or in another perspective, the manner in which organisational practices manifests in real life.

It is apparent from the summary of the two articles that the study by El-Awad employs deductive reasoning while the study by Liljenberg and Nordholm employs inductive reasoning. The research by El-Awad uses deductive reasoning because the author wants to test an already existing perception and practices, which are the frameworks and learning procedures by which business learning links at numerous levels on the company. The researcher goes ahead to use a well-known framework (TMS) to elaborate how individual base of knowledge are instilled in non-human features for a period of time before becoming entrenched in business practices. El-Awad goes ahead to perform a qualitative research to test the already theory, and to rule out if the findings support or refute the hypothesis. El-Awad in this scenario moves from a specific view to a more general perception, which is a critical feature of deductive reasoning. Liljenberg and Nordholm (696), on the other hand, use inductive reasoning because the researchers aim at creating a theory by shifting from more particular observations to wider generalisations. The systematic approach for analysing qualitative data adopted by Liljenberg and Nordholm presents the chance to perform a study that is guided by definite evaluation goals. It is the reason why they commence with examining the organisational procedure introduced in learning facilities to understand the link between ostensive and performative features of improvement task. The variations that emerge in the two articles with regard to reasoning approach provide valuable information to readers who gain guidance regarding inductive and deductive reasoning.

Question 4

Question 4 A

Conducting a quantitative study requires the researcher to be conversant with various terms such as population, sample, unit of analysis, and random sample that are vital aspects of any research, qualitative or quantitative. The following is a description of each of the terms that are necessary when performing a quantitative study;

Population

Population in the context of a research can be viewed as a comprehensive set of institutions, individuals, objects, or any other entities with similar features that are appealing to a researcher. The same attributes of the group make them different from others of the same kind (Balnaves and Caputi 127). The study population in many instances comprises of individuals who take part as participants or respondents (Balnaves and Caputi 127). The study population, for instance, may comprise of all children below five years old in a particular community. Population in research could also be fire fighters in New York, spiritualists moving to Mecca the Kingdom of Saudi Arabia or Kumbh Mela in India. Suppose a researcher aspires to carry out a quantitative research in the area of sustainable entrepreneurship the all learners in Swedish universities could be the potential study population. The population can either be finite or infinite. A definite population is one that can easily quantified whereas it is not easy to estimate a real figure or every person or object in an infinite population.

Sample

In a quantitative study or any other research such as educational or social research, practically it is impossible to the researcher to approach everyone or entity in a given population with the objective of collecting data. Instead, they choose and approach a particular section to represent the larger population to gather required data about the group (Balnaves and Caputi 129). Based on the outcomes, a researcher generalises the features of the representative illustration as the features of the population (Balnaves and Caputi 129). The relatively small group that represents a larger population is known as the sample. So ample can be described as the small group of a population chose to participate in a particular research (Balnaves and Caputi 129). A sample should adequately depict features of the intended population. The sample in this case could be several Swedish university students to represent the entire student population. Often the sample comprises of individuals or objects with different characteristics, but they may also be of the same nature. 

Unit of Analysis

The unit of analysis in a research is the primary component that the researcher is analysing in the research. For example, a unit of analysis could either be groups or individuals, or even an entire initiative. The unit of analysis identifies the “what” or “who” the researcher seeks to analyse in their research (Balnaves and Caputi 135). The unit in this scenario could mean the measure content that will be the foundation for decisions arrived at during the data analysis process (Balnaves and Caputi 135). The unit of analysis is an important aspect in a research because it allows the researcher to describe what is being researched as well as what particular elements are being examined. Moreover, knowing the unit of analysis presents a good chance to make timely preparations regarding the resources to use during the entire study (Balnaves and Caputi 135). An appropriate unit of study in the quantitative study in the area of sustainable entrepreneurship could be individuals to acquire personal views about elements of their education impacting their desire to establish a sustainable business.

Random Sample

A random sample in a research setting is a sample that is identified randomly, often using a random sampling technique. Random sample are suitable when a researcher wants to avoid any form of bias and other undesirable effects (Balnaves and Caputi 140). A researcher does not follow any particular order when selecting a random sample, and everyone has an equal chance of participating in the research. A researcher can create random sample by using the probability sampling technique known as simple random sampling (Balnaves and Caputi 140). Even though the chances of avoiding bias are high when working with a random sample, the researcher decreases their chances of recruiting participants who are well conversant with the topic or research questions, something that could harm the research significantly (Balnaves and Caputi 140). A random sample has a higher chance of giving a wrong responses, which may not only misguide the researcher, but also waste more of their time. Nevertheless, the approach is cost effective, which makes it a considerable approach for most researchers.

Question 4 B

A researcher should select the sampling method they choose to use very carefully to increase their chances for achieving a sample that is likely to give the most suitable findings. An appropriate sampling technique presents a better chance to arrive near-precise outcomes in little time (Taherdoost 20). Besides, using the correct sampling technique offers a suitable chance to attain higher measures of preciseness than without employing a particular sampling approach (Taherdoost 20). A right technique makes it possible to avoid data handling complications or monotony that are likely to emerge in a quantitative research, and which could tamper with the research outcomes.

A suitable sampling approach in this quantitative study in the field of sustainable entrepreneurship is stratified sampling where participants are first categorised into subgroups known as strata who all share similar characteristics. The primary goal or a researcher when using a stratified sample is to ensure all subgroups within a population get adequate representation in the selected sample (Taherdoost 21). Overall, stratified sampling offers adequate representation of the population because the data collector has dominance over the strata to ascertain that every subgroup has a share in the sample.

However, it is essential to be conversant with the possible merits and demerits associated with stratified sampling to avoid any possible inconveniency that could affect the quality and trustworthiness of the research. Taherdoost (21) thinks that compared to simple random sampling, a stratified sample can offer increased precision. Besides, because the approach gives increased precision, stratified sampling usually need a considerably smaller sample, which makes it cost effective (Taherdoost 21). The approach is more suitable because it is expected the measurement of response of interest to differ significantly between the various subgroups taking part in the exercise. The primary limitation of stratified sampling is it requires more commitment and resource input than the simple random approach (Taherdoost 21). Nonetheless, stratified sampling still remains the most suitable sampling strategy for the quantitative study.

Works Cited

Balnaves, Mark and Caputi Peter. Introduction to Quantitative Research Methods: An Investigative Approach. SAGE Publications, 2001.

El-Awad, Ziad. “From Individuals to the Organization: A Transactive Memory System Perspective on Multilevel Entrepreneurial Learning.” The Learning Organization, vol. 26 no. 6, 2019, pp. 617-630.

Evans-Winters, Venus, Edwards Erica and Esposito Jennifer. Futures of Data Analysis in Qualitative Research. Routledge Publishers, 2005.

Ferero, Roberto et al. “Application of Four-Dimension Criteria to Assess Rigour of Qualitative Research in Emergency Medicine.” BMC Health Services Research, vol. 18, no. 120, 2018, https://bmchealthservres.biomedcentral.com/articles/10.1186/s12913-018-2915-2

Harding, Thomas and Whitehead Dean. “Analysing Data in Qualitative Research.” Nursing & Midwifery Research: Methods and Appraisal for Evidence-Based Practice, edited by Zevia Schneider and Dean Whitehead, Elsevier, 2013, pp. 141-160.

Kitto, Simon, Chesters Janice and Grbich Carol. “Quality in Qualitative Research.” The Medical Journal of Australia, vol. 188, no. 4, 2008, pp. 243-246.

Korstjens, Irene and Moser Albine. “Series: Practical Guidance to Qualitative Research. Part 4: Trustworthiness and Publishing.” European Journal of General Practice, 24, no. 1, 2018, pp. 120-124.

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