Dmba103 - Statistics For Management Assessment Answer

Set 1

Question 1

Statistics indicate the study of numbers data, facts, figures, and measurements. It is utilized to change the raw numbers to useful information for pertinent users.

There is no doubt that statistics in modern business are extremely pervasive that it is certainly not possible to summarize. Statistics techniques and tools are being employed in modern businesses with the intent of solving managerial problems and decision-making. Moreover, it assists in business planning based on suppositions and forecasts. The major motive of business statistics is data gathering, enabling management to assess previous performances, predict future corporate actions, and run the company fruitfully. Also, it has become the base for sales forecasting marketplace patterns, risk navigation, varying client behaviors, determination of prices, and more. The most vital use of statistics is to evaluate performance whether it is the efficiency of a refined marketing approach, a new product line, or usually the efficiency of workers. Further, it helps companies in forecasting and navigating threats and refining the ROI (return on investment). Statistical analysis in modern businesses facilitates management to evaluate historic performances, foresee forthcoming corporate practices, and lead companies effectually. The statistics can define marketplaces notify advertising, react to variations in client demands, and set prices. Businesses in the current times might utilize statistics in market research and product development to explore more about their target people or schedule the launch of a novel good or service. It is frequently done utilizing questionnaires of random client sample sets to measure the market for a novel proposed service or good. An instance of the importance of statistics in finance can be its usage in the form of time series forecasting. A financial professional might use past statistics to predict the entire revenue, expenditures, novel clients, product sales, and more for a business (Black, 2023).

For example, The e-commerce company named Amazon has recommended its clients based on their previous orders and purchase patterns. In regards to statistical tools, the company uses ML (machine learning) and data analytics to stimulate their recommendation engines instead of impulsive suggesting goods to clients. Another such example can be Starbucks Company which utilizes an analytical strategy to recognize its forthcoming outlet locations. The company associate with a location analytics organization to explore the best outlet locations. It further constantly utilizes data to make informed choices about hunting novel clients, attaining client opinions, targeting marketing campaigns, and so more (Dey, 2021)

Question 2

Statistical Survey is defined as any structured inquiry created to get aggregated data that might be quantitative or qualitative wherein the business identities of the participants or people are in themselves of less prominence. It is further deemed a kind of investigation conducted by an individual or agent to study the nature of the unknown attributes of a population. The motive of a survey is to gather information to gratify a specific need (Story & Tait, 2019).

Data Collection Methods

Direct Observation Method

Direct observation indicates an underutilized and valued technique to collect assessment information. It is noteworthy that listening and seeing are deemed vital to observation. The observation mentioned offers the chance to document actions, behaviors, and physical aspects without having to rely on individuals’ readiness and capability to react to questions. This method is used when other data-gathering techniques like surveys are not successful. Moreover, it is used when the motive is to assess an ongoing behavior procedure or situation. For example, observing the teaching of a lesson by an educator to figure out if he delivering it with accuracy (Sileyew, 2019).

Indirect Oral Investigation

This data collection technique is usually employed when the participants are resistant to participate with the information for many causes. In this technique, the information is gathered from a third party who is directly or indirectly associated with the issue and has adequate know-how. The preciseness of the technique relies massively on the type of individuals interviewed. For example, this method can be used when we desire to know if an individual is addicted to gambling or not.

Questionnaire

The questionnaire is a data collection tool that entails an array of questions with the choices of answers, typed or printed in a sequence on a form utilized to acquire definite information from the participants. The questionnaire usually is administered in a standard pattern in a similar manner to the entire participants of the survey. An example of the questionnaire data collection technique can be used to attain useful feedback from clients after a purchase. Also, the questionnaire can be conducted to measure the efficacy of the client services and monitor client satisfaction (Rathi & Ronald, 2022).

Schedule

The schedule is considered the technique of gathering data and it possesses a range of statements, questions, and space provided to note down the answers. This technique can be used regardless of the literacy of the participants. Besides, there is direct personal contact of the participants with the enumerators.

Question 3

Quota Sampling

Quota sampling indicates the non-probability sampling method wherein scholars will formulate a set of people who are representative of a massive population. This sampling method is utilized when scholars possess definite constraints or criteria to conduct their study. Moreover, it is a quick, easy, and cheap technique of sampling. However, it leads to biased samples, less reliable data, non-generalized findings, can’t calculate sampling error, and more. For example, this sampling method can be used for obtaining a representative sample of pregnant women to examine patterns of smoking during pregnancy in London (Iliyasu & Etikan, 2021).

Systematic Sampling

This sampling means the probability sampling technique wherein scholars choose members of the population at a constant internally determined in advance. When conducted accurately on a massive population of a defined size, this sampling method can assist scholars, entailing sales experts, get representative outcomes on a large team of individuals without having to approach everyone (Bhardwaj, 2019). For example when the population size is given as 30000 and one desires to have a sample size of 600, then one requires to pick each 50th person (30000/600) on the list.

Snowball Sampling

This technique is considered a non-probability sampling method wherein presently enrolled research respondents assist in recruiting forthcoming subjects for a study. This is termed as snowball method since when the initial respondents recruit two more, and those two recruits bring in two others and so more, the number of respondents can rise exponentially like a rolling snowball. It is utilized when working with populations complex to find (Audemard, 2020). For example, scholars can utilize this technique to comprehend heroin users in two Australian cities. Consequently, scholars did not know more about their social settings and outlooks.

Cluster Sampling

This technique is a probability sampling method wherein scholars segment a massive population into small teams termed clusters and then choose randomly amongst the clusters to formulate a sample. This method is mainly utilized when the population, as well as the intended sample size, are specifically large. The main motive of this sampling method is to lessen the total number of respondents in a study when the actual population is extremely large to study as a whole (Berndt, 2020). An example can be when researchers desire to gather information about athletes in a specific city. In that case, he can segment the city into numerous clusters, each one entailing athlete from some part of town.

Set 2

Question 1

Business forecasting indicates the attempt to foresee the future. This entails utilizing a software, past data, corporate experiences, tools, and data analytics to reach a conclusion that tells what is expected to take place in the business. The businesses after comprehending the meaning of business forecasting can make sophisticated and intelligent choices that can influence their overall functions and profitability. The motive of business forecasting is to establish superior approaches based on such informed forecasts. It is deemed an estimate of forthcoming developments in business like expenditures, profits, and sales. It indicates the method of taking a viewpoint of things probable to form the turn of things in the predictable future (Gilliland et al., 2016).

The steps involved in business forecasting are as follows:

Comprehending the problem: The initial step in the forecasting procedure is the comprehending the actual issue that predictions are to be made. It can be said that management should know evidently the motive of forecasting. Predictions might be made with respect to technical situations, sales, choices of individuals, accessibility of finance, and more. A clear comprehension of the prediction scope might assist the management to investigate the pertinent information only.

Establishing the groundwork: This phase enables the management to comprehend what variations in the past have happened. The manager can utilize the historic data on performances to attain a speedometer reading of the present rate and how quickly such a rate is growing or declining. It might assist in evaluating the reasons for changes in the past.

Choosing and evaluating data: There exists a specific relation between the choice of statistics facts and figures and the determination of why corporate variations have happened. The statistics data can’t be chosen rationally unless there is an appropriate comprehension of the corporate variations. The causes of such variations will assist to choose the pertinent information. Statistical techniques might be employed to analyze the data.

Estimating forth coming events: The forthcoming events are measured based on the evaluation of historic data. The management should employ his historic experiences and judgments. It should know evidently what managers expect in the forthcoming in the view of entire corporate goals. The management must make a prediction of forthcoming business from numerous likely patterns revealed by the systematic evaluation of data. The predicted outcomes might be compared with real outcomes in the forthcoming. It might assist in improving the procedure of forecasting (Hyndman, & Athanasopoulos, 2018).

Question 2

The index number indicates an accumulated measure of the relative variation in a collection of presumably associated items. It is the tool that measures the degree of economic changes over a time period. Such numbers are statistical tools made to gauge the relative change in the level of an occurrence with regard to time, geographic location, or other attributes. The index number indicates the economic barometer since it offers a measure of the economic pressure on the clients directly or indirectly (Dorin et al., 2020). Another scholar Agarwal (2021) stated that an index number means a quantity that by reference to a base era, depicts by its variation, the changes in the magnitude over the time period. These numbers are expressed in percentages though do not utilize the sign of percentage. The index numbers are supposed to explore the changes in the impacts of such factors that can’t be measured directly. It is also defined as the single percentage that gauges the collective change of numerous variables between two varied times, places, or situations.

Utility of index numbers

• Index number does not just assist in the study of historic and current behavior, they have utilized also for predicting economic and corporate activities.
• The index number can help to gauge changes in the standard of living and the price levels.
• Moreover, governmental policies are formulated following the index numbers of prices, Such price stability intrinsic to financial and economic policies is based on such numbers.
• These numbers highpoint changes in the cost of living in the nation. These depict if the cost of living of the individuals is growing or declining. Based on such information, the workforce’s wages can be adapted consequently to save the wage earners from the difficulty of inflation.
• The index numbers are useful to provide information about the production patterns in diverse sectors of the economy. It assists in analyzing the real situation of diverse sectors that is whether production in a specific sector is growing or declining, or is constant.
• Index numbers enable comparative study with regard to place and time, mainly where units are varied (Oktaviarina et al., 2022).
• The cost inflation index assists in gauging the buying power of money at diverse times between varied regions. This evaluation assists the government to form appropriate policies to maintain or increase the standard of living of the individuals.

Question 3

Concept of Trend

In statistics, a trend indicates a slow change over a long time period, typically numerous years, usually linked with the structured reasons impacting the occurrence being measured. It is defined as a sequence of data points that gauge certain variables over an ordered time period. There is no doubt that a trend is a pattern in the time-series datasets which is utilized to define if the data is depicting an upward, or downward move for part or entire of the time series. The trend is deemed the quickest-growing category of databases since it is broadly utilized in numerous sectors to comprehend and predict data patterns. Besides, trends indicate a pattern in data that demonstrates the movement of a series to relatively greater or below values over a longer time period. It is observed of there is a growing or declining slope in the time series. The trend typically occurs for a certain time and then disappears and it doesn’t repeat. A trend can be an uptrend, downtrend, or stationary trend.

Methods of measuring trends

These are as follows:

• Graphical method: In this technique, the values of a time series are plotted on a graph by considering the time variable on the X-axis and the value variable on the Y-axis. A smooth curve is drawn freehand via the plotted dots. The trend line drawn above might be extended to predict the values.
• Semi-average method: In this technique, the series is segmented into two identical parts and the average of every part is plotted at the midpoint of their time duration. This technique is extremely easy to comprehend and does not need numerous calculations.
• Moving average method: It indicates a series of arithmetic means of variate values of a sequence. It is deemed another method to draw a smooth curve for time series data. This technique is more often utilized to eliminate seasonal changes. It is described as an average of a defined number of items in the time series that move through the sequence of dropping the topmost items of the prior averaged group and adding the subsequent in every successive average (Aghelpour et al., 2019).
• Method of least squares: This technique is most broadly utilized in practice. Moreover, in this technique, the sum of squares of deviations of the actual and computed values is minimum and the line attained by this technique is termed as the line of best fit. This also plays a vital role to find the trend values of the economic and business time series data (Beard et al. 2019).

References

Agarwal, S. A. (2021). Use of Statistics in Research. International Journal for Modern Trends in Science and Technology, 7, 98-103.

Aghelpour, P., Mohammadi, B., & Biazar, S. M. (2019). Long-term monthly average temperature forecasting in some climate types of Iran, using the models SARIMA, SVR, and SVR-FA. Theoretical and Applied Climatology, 138(3-4), 1471-1480.

Audemard, J. (2020). Objectifying contextual effects. The use of snowball sampling in political sociology. Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique, 145(1), 30-60.

Beard, E., Marsden, J., Brown, J., Tombor, I., Stapleton, J., Michie, S., & West, R. (2019). Understanding and using time series analyses in addiction research. Addiction, 114(10), 1866-1884.

Berndt, A. E. (2020). Sampling methods. Journal of Human Lactation, 36(2), 224-226.

Bhardwaj, P. (2019). Types of sampling in research. Journal of the Practice of Cardiovascular Sciences, 5(3), 157.

Black, K. (2023). Business statistics: for contemporary decision making. John Wiley & Sons.

Dey, S. (2021). Artificial Intelligence: A New Driver for Managing Customers in E-Commerce Smartly. In Applications of Artificial Intelligence in Business and Finance (pp. 29-49). Apple Academic Press.

Dorin, F., Perrotti, D. E., & Goldszier, P. (2020). Index numbers and their relationship with the economy. ECLAC.

Gilliland, M., Tashman, L., & Sglavo, U. (2016). Business forecasting: Practical problems and solutions. John Wiley & Sons.

Hyndman, R. J., & Athanasopoulos, G. (2018). Forecasting: principles and practice. OTexts.

Iliyasu, R., & Etikan, I. (2021). Comparison of quota sampling and stratified random sampling. Biom. Biostat. Int. J. Rev, 10, 24-27.

Oktaviarina, A., Pramoedyo, H., Astutik, S., & Fitriani, R. (2022, September). Comparison of spatial weight for consumer price index modeling in East Java using generalized space-time autoregressive. In AIP Conference Proceedings (Vol. 2633, No. 1, p. 020004). AIP Publishing LLC.

Rathi, T., & Ronald, B. (2022). Questionnaire as a Tool of Data Collection in Empirical Research. Journal of Positive School Psychology, 7697-7699.

Sileyew, K. J. (2019). Research design and methodology (pp. 1-12). Rijeka: IntechOpen.

Story, D. A., & Tait, A. R. (2019). Survey research. Anesthesiology, 130(2), 192-202.    

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