Doing Research in Business and Management - Assignment Example

Research Methods Name Institutional Affiliation Part A For the purpose of this question, it is of the essence to first understand what sampling is, the meaning of population, and a sample. To start with, a sample refers to a subset of events, people, or items from a larger set (population) usually collected to analyze or make inferences. On the other hand, a population refers to a set of people or individual units used by the research question to find out about something. In addition, sampling regards to a method that involves selecting particular units or individual units for the purpose of measuring from a larger population. For instance, an individual interested in knowing the average height of AFL players may decide to carry out a study by first identifying the population in this case AFL players. The researcher may then decide to collect data from a particular proportion or subset of the larger population (AFC Players) which we are referring to as the sample. The sample may include a smaller number of the whole group; the process of selecting a proportion to represent the whole team is what we are referring to as sampling. For instance taking AFL team as an example; the team has 700 players; we can make inferences by collecting raw data and analysing it by using the appropriate sampling technique for to chose a sample from the population, for instance, a sample of 300 players from the rest of the 700 players. Sampling is however divided into two types including probability/representative sampling and non-probability/judgemental sampling. Unlike non-probability sampling, probability sampling every unit present in the population has a chance usually greater than zero of being chosen in the sample hence as such the probability can be accurately examined. In light of such combinations of the traits, it is, therefore, possible for the technique to produce unbiased estimates that are not biased within the population. Probability sampling usually involves the use of randomisation. However, the technique tends to be more time consuming as compared to non-probability sampling. Examples of probability sampling include the cluster, stratified, systematic, and random as well as multi-stage sampling. Simple random sampling, however, it involves giving an equal chance of selection to all the subsets present in the population. Research might use this type of technique when it wants to exhibit top levels of unbiased and as well want to simply an analysis of the results. In addition, stratified sampling involves organisation into the population into different groups usually known as strata. Each stratum is further sampled independently by randomly selecting individual elements from each stratum. This type of technique is used when the researcher wants to draw inferences concerning particular subgroups that otherwise would have been lost if simple random sampling was used. On the other hand, non-probability sampling does not make use of randomization; instead, it gives a chance of selecting the sample purposively in order to reach the difficult to identify members present in the population. Various methods of non-probability sampling include the purposive sampling, snowball sampling, convenience sampling and quota sampling. To start with, snowball technique involves the first respondent referring to an acquaintance or a friend referring to friends and so on. However, despite the method being biased due to selection based on social connections, researchers may use it in studies where higher response rates are needed. Secondly, purposive sampling involves choosing a sample based on who the researcher thinks would be appropriate for a specific study. Researchers may use this technique in situations where there is only a limited number of people possessing expertise in that particular area of study. Also, the method can be used when the interests of the study are for a specific small group or field. Part B Question 1 In statistics, mode refers to the value that repeats/occurs most in a set of numbers or data. For instance, in data where one occurs three times, two occurs seven times, three occurs 14 times, 4 occurs times; then the mode would be3 since it repeats itself most than the rest of the numbers. In addition, mean refers to the sum total divided by the total number of values. It refers to the average of all the numbers divided by the total count of the entries. For example, if the sum total of the all the marks in the class of 20 students is 500, then the mean would be 500 divided by 20 students which are 25marks. On the other hand, median refers to the value present in the data that divides data into the half. Usually, median is regarded as the value that falls halfway in a set of data arranged in a manner from the smallest to the largest. In situations whereby the set contains an odd number of the values available, then the median value lies exactly in the middle. If the opposite happens such that the number of the values present is even, then the median is determined by averaging two numbers that are closest to the middle. For instance, if there are 51 values or entries in statistical data, the median would, therefore, be calculated by first of all arranging the values in an ascending order then selecting the value that divides the data into the half. In this case, the median would be the 26th term. If the values happen to be 50, then calculating median would take the 25th and 26th term, adding both values and then dividing by two. Correlation in the field of statistics refers to a measure that shows the extent/strength to which variables relate. Co-efficient of correlation, however, can only take on a value between -1 and +1. When the value is +1, then there is positive correlation meaning that variables are precisely related such that if values of one variables increase, the values of the other variables will consequently increase. On the other hand, if the value calculated is -1, then there is a negative correlation meaning that if values of one variable increases, then the those of the other variable will decrease significantly. Question 2 Quantitative data refers to that which can be expressed in terms of numerical numbers and is associated with a scale of measurement. However, not all numbers comprise of quantitative data such as tax file number. Quantitative data types include: i. Interval data which increase at constant intervals. However, it usually does not start from a true zero. An example is a temperature on Celsius scale or a gauge pressure ii. Ratio data which is a type of interval data. It is contrary to interval data since it has a true zero. An example is an absolute pressure iii. Binary data/dichotomous where the value of variables usually has two alternatives. For instance yes or no iv. Discrete data is a type of quantitative data where data points are separated or isolated by gaps. An example is case numbers of influenza v. Continuous data refers to a type of data where data points are usually part of a continuous range of values for instance height. Question 3 a. Questionnaires are the best fit in research where explanatory and descriptive data are required such as opinions or behaviours. In research that requires quantitative data, widespread sample, large samples, when the context is not new or even when the there is multiple languages present in the study; questionnaires are best suited for such studies. Questionnaires are easy to analyse and simple to administer making the method much applicable. b. Questionnaires can take the form of several types of questions depending on the research. First, the open questions offer the respondent a chance to give feedback using his or her own words. This type of questionnaire is usually used in research that requires descriptive answers. Second, list questions are the close-ended type of questionnaires that only require the respond to choose among the given options. These types of questions are commonly used in research that required a specific response or in large-scale surveys by minimising time consumed. Also, surveys that require a higher response are more suited to use these types of questions to carry out their study. Third, category questions, unlike open-ended questions, require the respondent to choose from the given options in the questionnaire. These types of questionnaires are used to gather specific pieces of data or information from the population. This type is usually used when the researcher wants to gather facts by limiting the respondents’ field of choice as well as the length of his/her response. Question 4 Literature review refers to a description of the previously conducted literature relevant to a specific topic or field and often provides an overview of the scope of the field of inquiry. A critical literature review is an in-depth examination or assessment of the literature relevant to the topic of the research. Critical literature review serves a fundamental purpose in the field of research hence its importance cannot be overlooked (Saunders, Lewis & Lewis, 2012). Firstly, literature review forms the basis of previous works of different researchers which consequently facilitate a clear understanding and conceptualization of the research topic in question and interpretation of the realized results. Also, it helps in developing new ideas and approaches through stimulation arising from the previously overlooked studies. A standard literature review gives a reasonable reason for choosing a particular research question (Boote, & Beile, 2005). Also, critical literature review helps the researcher perfect on previous mistakes by other researchers thus ensuring that the research remains at the top-notch. Secondly, literature review helps the researcher to narrow effectively down his or her research topic by assisting the researcher in defining it better and limit the research topic as well. In other words, it helps in converting tentative ideas into actual work. Thirdly, critical literature review suggests other approaches and procedures which the researcher might not be familiar with. Through this, literature review gives the researcher diverse useful knowledge relevant for perfecting on his or her research (Boote, & Beile, 2005). References Boote, D. N., & Beile, P. (2005). Scholars before researchers: On the centrality of the dissertation literature review in research preparation. Educational Researcher, 34(6), 3-15 Saunders, M., Lewis, P., & Lewis, P. (2012). Doing research in business and management: An essential guide to planning your project. Harlow, UK: Financial Times Prentice Hall Read More