Sampling and Population Representation

Question 1

a)

In any survey, population is utilized in order to define the subjects of certain study. It can be large or small in size and described by a variety of features. Population is utilized in order to observe conducts, trends and patterns, permitting researchers to draw conclusion regarding the features of the subjects of research. It is vital to comprehend the target population being studied, so as to understand the data. If the population is not described appropriately, it can result in data which are not useful for the study. There are certain restrictions for studying population, typically in that it is rare to be capable to observe every person in any given group. Due to this reason, researchers study the sub population and consider statistical samples of small percentages of bigger population to more precisely evaluate the complete range of behaviors and features of population at large (Taylor, 2019). A population is any group signify the group, who is subject to research, indicating that almost anything can make up a population as long as people can be congregated together by common feature. There are different kinds of population, which are significant for research, which are:

Target population: target population mentions to whole group of people to which researchers are concerned in making conclusion. Target population typically possess differing features and it is also termed as theoretical population. Accessible population: Accessible population is population to which researcher can implement the conclusion. It is a subset of target population and is also termed as study population. It is a kind of available population from which sample can be obtained. Finite population: Finite population is also termed as countable population where the population can be calculated. In short, it is described as population of every person i.e. determinate. For statistical evaluation, finite population is much beneficial in comparison with infinite population. For example, in this case, gauging the fellow colleagues is regarded as finite population. Infinite population: Infinite population is at times understood as immeasurable population, where the calculating is impossible. For instance, if the whole travelers is considered for holiday pay scheme it would become infinite population. Existent population: Existent population is described as population of concrete people. In short, it is the population whose unit is accessible in solid form. Hypothetical population: Hypothetical population is such population whose unit is not accessible in solid form, for example, population that consist of set of observations.

b)

For any kind of surveys, it is impractical with respect to time and budget and other aspects to survey everyone in the target population. Therefore sample is used for obtaining the opinions of people regarding a subject. The sample regarded as representative of the population. In order to be representative of population, sample require to match with population as much as possible. Sample is significant as it certify that every pertinent kind of people are included in the sample and that the appropriate mix of individuals are surveyed. If the sample does not become representative of population it become subject to bias. Certain group can be over represented and their views exaggerated while others may be under represented (Austin Research, 2020). In any research, resource is limited. Due to this reason, majority of research projects intend to obtain information from sample of individuals, rather than the whole population. The reason for significance of sampling is as follows.

Saves time: Communicating with everyone in a population requires time and invariably certain individuals will not react with the first effort at contacting them, indicating that researcher require to give more time in order to follow up. Sampling method is much quicker in comparison with surveying everyone in population. Hence, sampling saves researcher significant amount of time. In this context, non-random sampling requires less time than random sampling.

Saves money: The number of individuals a researcher communicate is directly associated with the expense of the study. Sampling saves money through permitting researcher to obtain similar responses from sample that they would receive from the population. In this context, non-random sampling is considerable inexpensive in comparison with random sampling, as it reduces the expenses related with finding individuals and obtaining information. Since every research is undertaken on a specific budget in mind, saving money is vital for any project.

Obtain richer information: At times, the objective of a research is to obtain little bit of information from considerable number of individuals, such as during opinion poll. Sometimes, the objective is to obtain considerable amount of information from just few individuals, for example in interview. Either way, sampling permits researcher to question respondents more questions and to obtain richer information than communicating ever person in a population (Moss, 2015).

There are two kinds of sampling methods that can be used, which are:

Probability sampling: In this kind of sampling, population sample cannot be chosen at the will of researcher. Sampling require to be done with certain procedures, which will certify that sample population contains fixed probability being incorporated. Such method is also termed as random sampling.

Simple random sampling: In this probability sampling, every respondent is selected wholly by chance and every sample of a population has equivalent possibility of being chosen. This method permits calculation of sampling error and minimizes selection bias.

Systematic sampling: In this probability sampling method, samples are chosen at regular intervals from a sampling structure. The intervals are selected to certify a proper sample size. It is frequently much expedient in comparison with simple random sampling and is simple to manage. However, this method can result in bias if there are fundamental patterns in sampling structure, such that the sampling method accords with periodicity of the fundamental patterns.

Stratified sampling: In this sampling technique, the population is first categorized into strata who possess similar features. It is utilized when it is expected that measurement of interest differs between diverse strata, and the researcher need to certify equal representation from every strata.

Clustered sampling: In this sampling, strata of population are utilized as sampling unit. The population is categorized into clusters, which are randomly chosen to be involved in the research.

Nonprobability sampling: In this kind of sampling methods, population sample is chosen at the will of the researcher. In this method human judgment is utilized for choosing sample and possess no theoretic foundation for evaluating the features of population.

Convenience sampling: This is the simplest nonprobability sampling, where respondents are chosen according to accessibility and will to involve. Convenient outcomes can be obtained from this sampling, but the outcomes tend to have biasness, as participants who involve in the study may be different than those who are not involved, and the sample may not be representative of other features of population.

Quota sampling: In this sampling respondents are provided quota of subjects of a stated kind to attempt to recruit. Whilst this method possess the benefit of being fairly straightforward and possibly illustrative, the selected sample may not be characteristic of other features.

Judgment sampling: This sampling method is also termed as selective sampling. It is subject to the decision of researcher while choosing sample. Researcher can obliquely select representative sample to adjust with the requirements or specificity of each respondent with certain features.

Snowball sampling: This sampling method is utilized for investigating hard to reach groups. In this method current samples are requested to nominate additional samples, known to them, so that sample size enhances like snowball (Check&Schutt, 2011).

Question 2

1)

In any research, data collection plays vital part for fulfilling the objectives. In this context, there can be two kinds of data, which are primary data and secondary data. The most vital aspect of primary data is that it is original and firsthand data. Primary data is obtained first time through researcher’s personal method and evidence. It is also termed as firsthand data. The method of assembling primary data is costly, as it requires human resources and investment. In this method, the researcher, manages and regulates the data collection procedure directly. Primary data is mostly gathered by methods like observation, physical evaluation, questionnaire, interview and focus group (Hox&Boeije, 2005). On the other hand, the most vital aspect of secondary data is that it is explanation and evaluation of primary data. Secondary data is secondhand information i.e. previously collected by other authors or researchers for their purposes. It is not based on the present research problem. This type of data is accessed from various sources, for example government publications, online sources, inner records of organizations, books, journals and reports among others. Secondary data collection method is inexpensive and less time consuming than primary data collection method. However, unlike primary data, this data may not satisfy the current research objective and may not be precise to the research problem. Following table demonstrates the key difference between primary and secondary data.

2)

Advantages of primary data:

There are various benefits of primary data, which are:

Specific to research subject: primary data is collected according to the specific research problem. Performing own data collection permits researcher to address research question and to solve the research problem, specific to the research subject.

Correctness: Primary data is much more correct as it is directly obtained from a specific population. One of the objectives of researcher while collecting primary data is to obtain correct data so as to arrive at appropriate conclusions. Therefore, biases are avoided at every cost.

High degree of control: Primary data has high level of control regarding the information i.e. been collected. The researcher is able to design the questions according to the research objectives and problems and therefore can get the appropriate information.

Up to date data: Primary data is great source of obtaining up to date data, because the researcher obtain it directly from the research area in actual time.

Ownership: Research obtain ownership over the primary data and is not usually shared with others. Hence, such data can stay hidden from other existing or possible competitors to be used.

Disadvantages of primary data

Expensive: Obtaining primary data is expensive, because researcher require to begin collecting data from beginning.

Time consuming: It requires long time in order to collect primary data.

Accessibility: Sometimes due to time, cost and other limitations it becomes impossible to conduct primary research. Sometimes obtaining primary data becomes too large to obtain by a single researcher.

Advantages of secondary data

There are various benefits of secondary data, which are:

Time saving: The first benefit of using primary data is that it saves time, and this is much obviousas researchers are depending much profoundly on digital information rather than printed materials contained in libraries. Traditionally, secondary data collection necessitates long time of library research. Networked and digital technologies have revolutionized this procedure. Therefore, precise data can be obtained through search engines. Furthermore, libraries in present days have become digital, which help to conduct more advanced searches.

Availability:Traditionally, secondary data were frequently restrained to libraries or specific organizations. Furthermore, general individuals frequently did not have access to these collections. Development of internet technology has been particularly revolutionary in this sense. By only having internet connectivity, these data can be accessed. With simple click, research can obtain huge amount of data.

Cost minimization: There is possible minimization of expense while using secondary data. One can easily obtain large data with only cost of paying the internet charges and electricity.

Extensiveness of research: The feasibility of research enhances when it is subject to secondary data. Secondary sources like government consensus and official registers are specifically useful for such research objectives.

Obtain perception from previous research: Reevaluating data can also result in unanticipated new findings. Returning to historical data help to arise with new pertinent conclusions or simply prove and confirm previous outcomes.

Disadvantages of secondary data

Unsuitability of data: Secondary data is collected with concrete thought in mind. In this logic, secondary data sources can give huge amount of information, but it might not be synonymous with appropriateness, as it is formerly collected to answer different research questions. Such data may not be appropriate completely for fulfilling the research objectives.

Low level of of control: Secondary data not always promise quality information. Therefore, while using secondary data, it require to be confirmed (Allen, 2017).

Question 3

To determine the effectiveness of the business it is vital that mean is determined so that the average outcome of the profit is being analyzed. The success of the business is being obtained from the value over a certain period of time.

a)

The main idea is to analyze the mean along with median for attaining the arithmetic average of the company scores for better sensitivity. The mean is used to attain the average profitability in the case of the John Lewis Partnership (johnlewispartnership, 2019). Means are better used to analyze the effectiveness of the company over the years. It has a strong major significance in the finance to determine the performances. The calculation of mean is done using the formula

Arithmetic mean= (x1 +x2+…… xn)/n

Number of years 5

Means = (289.8+ 250.5+ 452.2+ 103.9+ 117.4)/5

= £242.76

b)

Mode is one of the most vital factors that appears from a selected set of data. It is used to measure the central tendency. It is the most occurring value that helps to interpret the trend that is observed over the years. In this regard, as per the case of John Lewis partnership the profitability data is analysed to attain information about the trend and forecast (johnlewispartnership, 2016).

Mode= Observation with the maximum frequency

Mode is vital to determine the financial performances as it based upon the highest frequency. From the collected set of data, it is determined that the highest frequency is in the year 2017 with the profit.

The set of data of profits

c)

Standard Deviation- Standard deviation is about the analysis of risk that is being faced by the business. Standard deviation is being used to determine the variability and analyse the value from the financial set of records. It helps to determine the volatility that is being faced by the John Lewis partnership affecting the business. It is used to determine the dispersion of the data set that is usually relative to the mean (johnlewispartnership, 2017). The volatility is more when the standard deviation is high and the risk is high with lower deviation.

The calculation

Here the standard deviation for the company is low.

Question 4

Management Information Systems (MIS) is being used by the business for making effective decision making so that the process is simple and effective. MIS was used by leaders of the organisation for making decision based upon the variety of information. MIS has a significant role to play in the business organisation as it has the ability to influence decision depending upon the requirements and problems that occurs. For the management information plays a strong role so that the functions are carried out effectively. The success of the management is usually based upon the level of accuracy of information and it is being presented in the form of reports to enhance benefits without misleading data. When it comes to making sound decisions management needs information which is efficient and effective so that the irregularities faced by the business are reduced (Meiryani & et. al. 2020). The perceptive is true as MIS encourages increasing productivity and contributing to the attainment of the organisational goals. Decision making is being influenced based upon several factors that impact the process of based upon the problems. The effectiveness of the use of MIS is being based upon several aspects as MIS is being defined as a system which is using to offer valued information for better decision making. MIS is one of the systems which uses database of the organisation to offer valued information so that the problem structure can be met. MIS is being used to support the decision making process to generate better understanding through effective planning and operational planning along with control. MIS as mentioned is gaining importance as it focuses upon proper planning so that the managers are assisted for making vital decisions that positively influences the business (Alter, 2021). Contextually, decision making model is being used for several reasons and one aspect that is being considered upon is the models that impact the process such as the rational model, political model, anarchy model along with process model. The value of decision making is based upon the quality of information and therefore the role of MIS is important to make better decision making through the attainment of structured information (Notesmatic, 2021). There are benefits that are attained owing to the use of MIS that impacts the organisation decision making. The management provides valuable support in the process of gathering credible and reliable information so that the designing of the actions for the decision making is effective thus helping the process of monitoring. Furthermore, the agreement is based upon the fact that MIS supports the various level of decision making to obtain and store information relating to better problem standardisation as per current situation (Linton, 2019). The feedbacks that are attained also are taken as a part of the information so that the decision making is taken in the most effective manner. Decision making is regarded as a process that is being used to identify and select actions that are important to solve particular problems in relation with MIS. The process that makes the perspective effective is based upon steps:

Intelligence- The process of investigation contains vital examination that is based upon data which are attained both the ways such as predetermined way and in a special way. The data provided requires an information system that leads to the examination of data that requires proper testing regarding the situation and also reflects about the clear intention through proper communication. This clearly helps to indentify the issues that are faced by the organisation top level so that the issues faced can be addressed.

Design- A proper decision model is required in order to process the data so that the alternative solutions are made that helps in the effectiveness (Meiryani & et. al. 2020).

Choice- MIS becomes effective when the designs are well framed thus encouraging the process of decision making through proper feedback along with assessment. However, there are problem solving aspects that impact the process of decision making through situation investigation such as formulation of problems, identification of the decision objectives along with diagnosis of the causes (Meiryani & et. al. 2020). For the success of the business decision making plays a pivotal role and it is being helped with MIS. Thus, the decision making model with MIS is depicted through the help of the diagram below:

The perception to agree to the fact is based upon the aspect that MIS is one of the most useful tools for decision making as it monitors the process and disturbances during the course of actions thus helping to control. It also impacts the human along with material resources thus helping the process of decision making (Ghaffarzadeh, 2015). The main factor behind the use of MIS is that it helps to manage the flow of information for better decision. MIS is also used and is stated effective as it helps in the process of transformation. This is being depicted through the help of the diagram below:

The concept of MIS is renowned, and it guarantees viable decision in the business as the system is supported based upon information system. MIS has a role towards business analysis in the organization that supports operations, management along with decision making functions so that information are attained timely, and the decision making is effective to carry out the operational goals. The MIS has gained relevance in the business study as tends to meet the objectives such as:

For making sound decisions MIS is being used so that the decision is effective as the approach is systematic and is holistic in approach, the MIS follows the top down approach so that the overall business objectives are met. The MIS acts as a need based approach which is effective to ensure strategic planning along with management control so that the information caters to the specific needs thus helping in the process of decision making. Moreover, integration is being used so that the process of information is meaningful helping to improve the long term planning (Geek Tonight, 2021). The decision making is made owing to the use of MIS in the process of decision making as it helps to improve customer satisfaction through proper decision making. The quality of information attained is important to make decisions that are responsive to meet the competitors and attain advantage. The operational efficiency along with flexibility is attained through the use of MIS. Both internal and external communication is well planned due to the integration of MIS thus improving supervision and control (Hearst, 2019). One of the main roles of MIS is to make proper decision as the gathered data are relevant and helps in proper coordination to mitigate the problems. The validity and accuracy of the decision making is vital as it tends to manage the operation along with sustainability (Leaf Group, 2019). The decisions are effective as perceived because it is based upon the knowledge that helps employees of the organiosation to perform well. This integration with the organization of MIS helps to generate useful decision so that the efficiency and effectiveness of the business is improved.

References

Allen, M., 2017. The Sage Encyclopedia of Communication Research Methods. Sage.

Check, J.&Schutt, R. K., 2011. Research Methods in Education. Sage.

Ghaffarzadeh, S.A.M., 2015. Decision Making Based On Management Information System And Decision Support System. Journal of Management Research and Analysis, Vol. 2, No. 1, pp. 98-107.

Hox, J. J.&Boeije, H. R., 2005. Data Collection, Primary vs. Secondary. Encyclopedia of Social Measurement, pp. 593-599.