Question 1
Typically, a business research report includes six main sections. Analyze the function of each section. Which sections might you omit in a trade newspaper research report, and why?
Sections of a business research
Introduction
An introduction is the most important is a crucial section in any writing since it briefs an outside observer on the general view and purpose of a particular article, book, or any writing. However, since in most cases the researchers do not often know the outcomes of research, they are usually addressed by the problem of creating a structured introduction. Therefore, background information becomes an important ingredient that lures readers to focus on the entire research process. Moreover, the research problem and the research objectives are outlined in the introduction part of the report. The two terms are usually confused, but they refer to different things. The research problem indicates the gap that necessitates the study. On the other hand, the research objectives describe the aim of the research. Business research objectives vary considerably in relation to the business and the type of research that is involved. The researcher also provides preliminary research assumptions that guide their research into the next chapters.
Literature review
Literature review comprises of scholarly publications from various authors concerning a particular subject and providing knowledge and substantial findings on it. Additionally, literature review includes both theoretical and methodological contributions about a specific topic. This section acts as a secondary source for data collection and analysis that guides the researcher to conduct his/her study. Literature review entails looking at various contributions by different authors and highlighting on what they put forward about the subject matter.
Method section
This is the point at which specification of the method that is most convenient for the research is stated. Additionally, the tools for data collection such as interviews and questionnaires are mentioned in the method section. The most remarkable thing about this stage is that one can forecast the environment under which the research was undertaken as well as familiarise with the different materials, tools, and methods that were used for research. The researcher also provides a justification of the methodology explaining why they took a particular approach in their study. Moreover, model specification is critical to mention at this section. Usually, this entails developing a conceptual model that represents the entire system under study. A conceptual model comprises of concepts that help people to get in the know as well as well as understanding the representation of the model. The model embraces a general hypothesis which acts as the main purpose of undertaking research. A hypothesis is a proposition that explains a particular phenomenon of interest that necessitates the study. A research strategy is a plan of action that researchers use to address and come up with possible solutions to an existing research question. Selection of the sample size is also important in research since it saves on both time and other resources such as costs of undertaking research on the entire population. Selection methods are diverse to include random, stratified, systematic, and cluster sampling.
Analysis
The appropriateness of this section largely depends on the methodology. The analysis involves breaking down a topic into sub-units to have a clear understanding based on the findings guided by the methodology. If a research took the form of quantitative technique, presentation of results would be in quantitative terms which sometimes are difficult unless one is familiar with quantitative arrangements. The important thing about this section is that it helps in explaining the findings of the business research. The small sample sizes selected during the methodology stage can be analyzed using a t-test, ANOVA, or any other appropriate test. The t-test uses the statistical examination to calculate the mean differences of two population distribution whose variance is unknown.
Discussion
The main purpose of the discussion stage is to highlight the major statistical findings from the result section as well as interpreting them. The initial stage of the discussion is to restate the overall purpose of the study and then explaining the major findings as related to the overall purpose of the study. Above all, it also includes an explanation of the statistical findings and how such findings relate to the purpose of the study and previous studies. Importantly, all explanations must have evidence from the results of the data analysis.
Conclusion and recommendations
The conclusion unites all previous chapters the discussion of the business research report. This chapter must have direct connection to the data collected and analysed during the research. Only key points need to be included in this section. Giving out recommendations involves highlighting on the practical steps that need to be undertaken to implement the key findings of the research study. Additionally, the researcher suggests areas of future studies based on the limitations and findings of their research.
Sections to Omit in a Newspaper Research Report
The most critical consideration to make in a business report is the audience that is targeted and their preferences. Based on the requirements of a trade newspaper research report, it will be appropriate to eliminate the methods and literature section. Most readers would focus on reading the findings and discussion section although the former can be integrated in the former. Depending on the length of the report, the discussion can base the presented findings on previous literature directly without a literature review section. Instead, links to the mentioned texts can be provided I the report for readers who would prefer reading what has already been presented by other researchers on a related study. Therefore, a good introduction, discussion with integrated findings, and conclusions section would present a good newspaper research report without necessarily providing the methodology and literature sections.
Question 2
Discuss how statistics can be used to describe the central tendency and spread of quantitative variables in business
The four main measurement scales used in statistics include nominal data, ordinal data, interval, and ratio data.
Nominal data
This is the kind of data that is given in exclusion of any quantitative terms. The main task of nominal scales is labelling of variables. Examples of nominal data may include gender, colour, and place of residence none of which include any numerical figure.
Advantage: Data categories are represented by labels ensuring no misidentification. Also, there is no natural order of classification and this safe on time.
Disadvantage: Data categories do not follow a logical order even when the labels are not quantified.
Ordinal scale
In ordinal scale, there are no numerical values attached to the ordinal set but what matters most in this type of measurement scale is the order of events. As a result, ordinal scales are used to measure non-numeric values such as satisfaction and happiness feeling.
Advantage: Data categories are ranked through labeling as low, medium or high, and one category in this ranking is better than the preceding element.
Disadvantage: Too much time is wasted on ranking, and it is also subject to biasness because the responses are often narrow about the question.
Interval scale
This is the type of measurement that gives a numeric difference between any two variables. The most outstanding thing in this measurement is that one does not only the interval but also the actual difference in numerical value. Examples include human body temperature, a melting point of water.
Advantages: Apart from incorporating all the features of ordinal scale, it also includes a constant value between variables. Additionally, data is classified according to the amount of characteristics they possess.
Disadvantage: Sometimes an equal difference in the characteristics is not represented by an equal difference in the measurement as data may be distorted.
Ratio scale
This is the type of scale whereby the numerical values from interval scale are expressed as a ratio. The most significant thing about ratio scales is that it provides a range of possibilities that are significant in statistical analysis. Other measurement tools such as mean, median and mode as well as the measure of dispersion can also be calculated using the ratio scale.
Advantage: It contains all the characteristics of interval level.
Disadvantage: It is prone to biasness and data distortion. It is also time-consuming in the calculation of data ratios.
Skewness
Skewness in probability theory and statistics refers to the asymmetry of data in a given probability distribution about its mean. We can have a positive or negatively skewed curve. A positively skewed curve is one where the mean is greater than the median, and the right tail is longer. Negatively skewed curve occurs when the median is greater than the mean, and the left tail elongates longer.
Kurtosis
This is a term that is used to describe skewness of observed data around the mean. Kurtosis can either be mesokurtic, leptokurtic or platykurtic. Mesokurtic distribution has fatter tails than all the others and a lower peak while leptokurtic has thick tails and a thin and high peak. Platykurtic distributions have slender but smaller peaks than mesokurtic.
Issues of survey design
There has been a general trend in the overall survey design which requires changing. Quite often, individuals who were not connected to the planning and designing process are given the mandate to analyze the data. Fundamentally, research instruments used also pose a major threat to the scale of data collected. Thus, if large scale data must be collected, it means that research instruments need to be improved to cater for powerful statistical inference despite the trade-off between the costs of data collection and the scale together with the accuracy of the data harnessed.
Question three
Discuss with examples, how research philosophy may assist you to choose a research strategy, and to collect and analyze data.
Philosophical research refers to the advancement of rational reasoning that creates room for contemporary ideas with previously established thoughts through structural phases. There are four classifications of research philosophy, and the choice of a specific classification must be outlined. As such, the choice of a research philosophy iscritical as it acts as a guide towards adopting the best research strategy. The direction of a research philosophy is from the source to nature and finally the development of knowledge. By source means, that, every research philosophy must have an origin from where the research process starts; as such, it is from this source that development of ideas spreads. The source acts as the core from where ideas originate from and then spreads to the periphery.
Research philosophy involves an individual’s awareness of the topic under research and proper formulation of beliefs in addition to a list of assumptions. Each stage of research philosophy must comprise a set of assumptions concerning the sources and nature of knowledge. It is, therefore, the philosophy of a study that portrays the researcher’s important assumptions, which acts as the basis for the research strategy. There are four principle methods of data collection and analysis in research philosophy. These include pragmatism, positivism, realism, and interpretivism. In pragmatism research philosophy, ideas and concepts are accepted if they only support a particular action. The outstanding characteristic of this type of philosophical research is that the researchers acknowledge that the world is dynamic and diverse. As such, they believe that there are various ways of interpreting the world and that; there is no single, accepted, and conventional standard for defining the world and undertaking research. As a result, they acknowledge the multiple existences of different ways of giving realities of the world.
The most remarkable ingredient of pragmatism research philosophy is the research questions which come out as the main determinant of the research philosophy. Research philosophies can combine the attributes of both the positivism and inter-pretivism positions within the extent of a lone research according to the nature of the research question.
Positivism research philosophy acknowledges the fact that all factual information that is acquired through observation inclusive of the measurements used is trustworthy. In this regard, the researcher is usually objective in approach to this type of research philosophy since he or she is limited to data collection and interpretation. The most outstanding feature of this research philosophy is that; the findings are both observable and quantifiable. The quantifiability of observations in positivism by itself leads to analytical statistics. Further, most positivists are of the belief that knowledge emerges from individual experience.
In data collection and analysis, positivism looks at the observer, human interests, explanations, research progress, concepts, units of analysis, and generalization. The observer or researcher must be independent to avoid distortion of the data collection process. The main argument with positivists is that human interests are the main drivers of science and should at first be irrelevant. They add that explanation of the occurrence of events must have causality. Indeed, the main aim of positivism research philosophy is to increase the general understanding of the situation. Moreover, they purport that research progress should have hypothesis and deductions, which rest on the fact that; the information is rich in data from which conclusions are abstracted.
The main methods used to collect data in research philosophy study include primary and secondary. In secondary data, the main sources of data collection are the newspapers, magazines, journals, and online portals amongst others. Contrarily, primary data involves both qualitative and quantitative techniques. In the quantitative analysis of data, the main methods of data collection include the use of close-ended questions, correlation, and regression by use of mathematical calculations. Qualitative entails the use of nonmathematical calculations and is usually encompasses the use of words, sounds, feelings, and emotions.
