business statistics assignment help australia

business statistics assignment help australia

The Importance of Business Statistics in Decision-Making: A Comprehensive Guide for Students

1. Introduction to Business Statistics

Every discipline of science usually presents two aspects: those of natural laws and regularity of actions such as relations, size, motion, etc., and another is the theory and principles to deal with these relations and regularities. The laws and regularities of the first aspect are discovered or explored with the help of statistical tools such as collection, classification, tabulation, graphical presentation, inference, and estimation of certain characteristics, etc. This is the domain of business statistics. Business statistics help in providing objective of the policy measures. It aids in presenting complex economical problems in a simple and understandable manner. It helps in developing expertise and competitions. It tests the effectiveness of policy measures.

Business statistics refers to the application of statistical tools and techniques to business and managerial problems. Statistics are numerical statements of facts, in any department of inquiry, placed in relation to each other. Business statistics helps us in taking better decisions with the help of statistical techniques to smoothen the process of analyzing complex data, even of an uncertain event, resulting in predicting events to shape better business strategies. It determines the relation of a selected business variable with all the variables with which it is associated and evaluates the strengths of the relationship. It brings rationality in the thought process.

2. Key Concepts and Techniques in Business Statistics

2.1.1 Mean The average represents one of the most common numbers in describing the behavior of an item. Suppose that a business statistician has been asked by a shipping company to determine the mean or the satisfaction level of its users. The satisfaction level rating of the users mainly ranges from 1 to 10. The satisfaction levels of 5 randomly selected users are 7, 8, 8, 9, and 7. The average level of satisfaction can be computed by summing the ratings provided by the users (sum of the satisfaction score = 7 + 8 + 8 + 9 + 7 = 39) and then dividing it by the number of users (number of users is 5). Hence, the mean rating should be (39/5 = 7.8). Consequently, the mean level of satisfaction is equal to 7.8. This implies that, on average, users are satisfied.

2.1 Basic Descriptive Statistics Techniques in Business Studies Basic statistics tools and techniques are at the heart of any business, economics, or management students since these are vastly used in classroom activities, assignments, projects, and internship reports. The typical descriptive statistics techniques include mean, measures of variability, percentile, quartile, box plot, frequency distribution, bar chart, pie chart, scatter plot, line graph, correlation, simple linear regression, etc. Following is a brief account of the above-mentioned techniques of descriptive statistics:

Business statistics provide extensive tools and techniques to make managerial and business decisions. These tools and techniques allow decision-makers to take an effective course of action. Broadly, the techniques fall into two categories: descriptive and inferential statistics. Descriptive statistics summarize the characteristics or behavior of a dataset. It includes techniques like mean, median, mode, range, variance, correlation, etc., using tables, graphs, and charts. Inferential statistics, on the other hand, study the statistical relations among the variables to be inferred from the population. It uses data from a random sample to answer questions about the population from which the sample is drawn. The data required in business statistics is classified under two categories: qualitative and quantitative data. Qualitative data contains characteristics not relevant for mathematical computations, while quantitative data contains numerical measurements of the characteristics of an item.

3. Applications of Business Statistics in Various Industries

3.1. Production-related applications 3.2. Marketing-related applications 3.3. Finance-related applications 3.4. Human resources-related applications 3.5. Research and development-related applications 3.6. Risk management (insurance)-related applications 3.7. Miscellaneous applications

To have a better understanding of the applications of statistics in business, students ought to be exposed to situations in many areas of commerce in which the thought process may be helping organizations to make better decisions. Here are some of the interests:

3. Applications of business statistics in various industries

In this chapter, we develop our arguments in terms of the importance of statistics in the business context in more detail. We look at common problems that are encountered and consider and apply solutions. This chapter is intended for students following a second statistics course at tertiary education institutions or universities.

2.1. Introduction

2. The main applications of business statistics in the real commercial context

4. Challenges and Best Practices in Using Business Statistics

Unconservativeness of statistics are the classical challenges discussed within the context of decision theory. Business statistics is a powerful toolkit for scientific decision-making process in business and economics. All decision support systems have business statistics as part of the system. Computer hardware, software, and information are the other three. In order to have successful results in decision-making, business administration and economics students need to have difficulty understanding business statistics and how to use it.

In this section, common challenges arising from the use of business statistics within the context of many other decision-making techniques and best practices in using business statistics as part of a scientific decision-making process are explored. Common challenges include using historical data for predicting future values, the additive nature of random variables. When the work is done, misunderstanding of confidence intervals and thinking that a normal distribution curve always fits our data are discussed in terms of statistical problems. Deriving a sound statistical model, interpretation issues of statistical measures, and complex calculations in constructing models are enumerated nonstatistical difficulties. All of these are integrated within the guidelines on how to use business statistics to pave the way for better decision-making in business and economics.

5. Conclusion and Future Trends in Business Statistics

In conclusion, business statistics will help people and organizations in better decision-making for better business activities. Different roles for people transverse in business from statisticians to managers and their stakeholders are discussed. The potentials of Big Data are going to improve business statistics in terms of organization and system of work. Six Sigma revolutionizes the businesses with a more sophisticated way of problem-solving from data, together with the more specialized roles, tools, and knowledge. More than expected, problems will always pose the world with more challenging, thrilling adventures awaiting the experts to kick out from business. To maximize business potential, one must understand them and practice them efficiently. Business statistics begins when data related to business or the economy matters. The bottom line is explained with an alarming prediction if business professionals do not become better consumers of business statistics.

This chapter presents the importance of statistics and the application of quality tools in statistics-driven decision-making in business. For quality, data, and the results drawn from these data play an important part. The successes of Western businesses in the late 20th century reinforced the belief in the significance of statistical quality control. Increased competition is forcing many firms to reduce costs. The simplest way is to reduce quality control and seek to make good the reduction by inspection. This can put customers off soon and reduce income. The cost of this approach is impossible and would put insurmountable burdens on inspection. A better approach is to reduce internal costs without compromising quality in use. This, in turn, calls for improvements in costs and quality, in one word: business statistics.