Unit 6 Business Decision Making Assignment Copy
Introduction
This report details the business decisions made by BRIT College. The college wants to increase enrollment, so a study must be conducted to determine the preferences of current students. Additionally, the college must build more classrooms in order to accommodate more students, so choosing the right project will also aid in better decision-making.
Task 1
1. Research strategy
Data collection: Data collection is crucial to research since the success of the entire project depends on understanding the preferences of the general public. Both primary and secondary data must be gathered to enable more informed business decisions. The information for this study on recruiting students to BRIT college will be gathered in the manner listed below.
Primary data refers to information that is gathered for the first time specifically for a study project. As the researcher collects data for a specific study project for the first time, it is also known as first-hand data. Surveys, sampling, questionnaires, and other sources of primary data are all possible (Curstedt, 2013).
Secondary data are previously utilised data that are employed once more for a certain research project. Instead of collecting this information for the first time, the researcher uses data that has previously been made public for this inquiry. Journals, newspapers, magazines, essays, and other sources of secondary data are also acceptable.
Plan for data collecting to aid BRIT College in achieving its objectives
1.2 Sampling methods and survey methodology.
Survey technique is the process of using surveys in a certain type of study. This approach involves selecting a group of targeted students, gathering data from them as a sample, and then analysing the results. These sampling techniques come in two varieties.
unbiased sampling: In this approach, locusassignments are chosen based on their lack of likelihood, or you might say that the locusassignments gathered in this way are based on the researcher’s judgement.
Probability sampling: In this sampling approach, allocations of locations are selected based on their likelihood. This sampling technique is based on random sampling, which demonstrates that each sample has a possibility of being chosen. Four additional categories are created using this methodology.
Every item has a probability of being chosen as a sample in a simple random sampling.
Individuals are sorted into groups via a systematic sample, after which locus assignments are gathered (Kaufmann, 2016). Stratified sampling: Any subgroup within the population is randomly chosen in this sampling method once it has been separated into groups.
Task 2
2.1 Calculation of mean, mode and median
Mean: A sequence of numbers are added together and then divided by the sum of all the numbers to determine the mean, which is a measure of central tendency. It also goes by the name “arithmetic mean” (Sinova, et.al, 2014).
As a result, 34.5 is the median, or the midpoint of the achievement.
The greatest value in the series is known as the mode, which is also a measure of central tendency (Cardinal, 2015).
The median for the above table is 40 because the highest frequency in the table is 47.
The highest achievement is 47 as a result.
2.2 Results evaluation
The graph was prepared with an idea of 50 students from the college in mind, making it simple for us to calculate the mean, mode, and median for the results of 50 students. The results of the calculations above show the relationship between the students’ satisfaction and their achievement, which are represented by their scores.
The average grade received by 50 pupils, as determined by the aforementioned calculation of the mean, was 33.2. The mode, which displays the maximum frequency of the marks that students are earning, reveals that 40 is the mark that students are earning the most frequently. The median displays the midway value of the students’ grades, which is 34.5.
2.3 Measures of dispersion
Standard deviation: The standard deviation is a measurement of how widely the data values can vary. This demonstrates the connections between the data values (Manikandan, 2011).
The above table’s standard deviation is 8.09, as a result.
Standard deviation may be computed as the complete square of variance because it is essentially the square root of variance (Koacz & Grzegorzewski, 2016).
The variance for the aforementioned table is 65.38.
2.4 Calculation of quartile, percentile and correlation
Quartile: Quartile is sometimes referred to as quartile type. The midpoint of the series, known as the median and denoted as Q2, the midpoint of the minimum number and the median, known as Q1, and the midpoint of the greatest value, known as the Q3, are used to create the ranking set of data values.
The term percentile, also known as centile, is used to denote the number that represents a certain proportion of observations in a series (Abid, et.al, 2014).
Correlation: Correlation demonstrates the connections between the values of data in a series.
Task 3
3.1 Graphs
The results of an analysis of 50 students and 10 graduates with relation to their satisfaction and success at BRIT college are shown in the figures above.
Pivot point 3.2
In this research trend line is prepared with a view to identify the trend in the responses of the students in regard to their satisfaction and achievement in BRIT college (Maurya, et. al, 2014).
Task 4
4.1 Support to decision making process
Every organisation may make better decisions thanks to decision-making tools, which help them to analyse circumstances appropriately and improve their own decision-making processes. The following are some of the resources that BRIT College uses to assist with college decision-making.
Transaction processing systems (TPS): A TPS is a piece of information that is utilised in business transactions to improve the speed, accuracy, and consistency of data. Since they are utilised at schools at an operational level to keep attendance sheets and tracking sheets, it aids the business in using the information more effectively and improving decision-making in the institution.
These systems assist in maintaining student and instructor attendance records so that the college can monitor the overall performance of both the students and the professors.
Management information systems (MIS): A MIS enables management to store information about management in relation to management-related areas such as HR databases, Intranets, online marketing, etc.
Since they are utilised at schools at an operational level to keep attendance sheets and tracking sheets, it aids the business in using the information more effectively and improving decision-making in the institution. These systems assist in maintaining student and instructor attendance records so that the college can monitor the overall performance of both the students and the professors.
Unit 6 Business Decision Making Assignment Copy
Management information systems (MIS): A MIS enables management to store information about management in relation to management-related areas such as HR databases, Intranets, online marketing, etc. This management information system assists the college in storing information and knowledge related to management in the database so that all activities of the management team members can be kept on a single platform for proper tracking. It also assists in identifying each management team member’s performance, allowing the college to make better decisions based on the data stored in the system.
Executive information systems (EIS): This information system is useful at the strategic level of management to help them develop better college-wide plans as well as to assist them in making better decisions based on those strategies. These EIS are useful for managing information to hold meetings with stakeholders, attend conferences, and manage information pertaining to senior managers in a secured manner so that the information can be managed in proper ways and is managed properly and there is no risk associated with the information.
References
Abid, M., Abbas, N., Nazir, H.Z., Nawaz, T. & Sherwani, R.A.K. 2016, “Improved Ratio Estimators for the Population Mean Using Non-Conventional Measures of Dispersion”, Pakistan Journal of Statistics and Operation Research, vol. 12, no. 2, pp. 353-367.
Cardinal, L.J. 2015, “Central tendency and variability in biological systems”, Journal of community hospital internal medicine perspectives, vol. 5, no. 3, pp. 27930.
Unit 6 Business Decision Making Assignment Copy
Curstedt, T. 2013, “Synthetic surfactant: primary data”, Early Human Development, vol. 89, pp. S111-S112.
Ferrigno, P. 2014, “Current research report”, Australian Journal of Acupuncture and Chinese Medicine, vol. 9, no. 1, pp. 32-33.
Kaufmann, E.N. 2016, “Survey this”, MRS Bulletin, vol. 41, no. 3, pp. 263-264.
Kinsella, J. 2011, “Survey”, Overland, , no. 202, pp. 78.
Ko?acz, A. & Grzegorzewski, P. 2016, “Measures of dispersion for multidimensional data”, European Journal of Operational Research, vol. 251, no. 3, pp. 930-937.
Manikandan, S. 2011, “Measures of dispersion”, Journal of pharmacology & pharmacotherapeutics, vol. 2, no. 4, pp. 315-316.
Maurya, M.R., Paritosh, P.K., Rengaswamy, R. & Venkatasubramanian, V. 2010, “A framework for on-line trend extraction and fault diagnosis”, Engineering Applications of Artificial Intelligence, vol. 23, no. 6, pp. 950-960.
