Statistics for Management

Assignment Brief

Unit Number & Unit Title Unit 31: Statistics for Management

Scenario

You are working as a Data Analyst for your organisation. Your supervisors want to understand the value and importance of statistical management and how it can be used to resolve challenges faced by businesses. You will need to reference how a company utilises statistical management to achieve business objectives and you will need to analyse how statistical management interrelates with other business functions to deliver results.

Task 1

Individual Presentation. 15 minutes incl. Q&A session

Prepare your presentation, addressing the tasks specified below.

PART 1 (theory) You are tasked to explain the value and importance of statistical management:

1. An introduction to statistics; definition, key characteristics, overview of methods etc.

2. Sources and types of data and information businesses can access.

3. The difference between a sample and a population.

4. The value of employing statistical methods when meeting business objectives and achieving competitive advantage.

5. Explanation of the difference between descriptive and inferential statistics and the implications for business intelligence.

6. Provide examples of analysis of given sample sets of data that could be used by the organisation.

7. Be prepared to answer questions related to your analysis and explain all information included on your slides. .

PART 2 (application)

You will be given an Excel document containing monthly adjusted share price information of Apple, Microsoft, Netflix and Amazon for a 5-year period. In the same document, you will also be provided the NASDAQ’s composite index IXIC’s monthly adjusted closing data. You need to choose two of these companies for your analysis and presentation. You need to also use IXIC’s data for further analysis. In addition, you will be given the last four years of revenue, cost and profit information with regards to these companies. You are required to utilise descriptive and inferential statistics methods in this task.

1. Evaluate the differences between descriptive and inferential data.

2. Using sets of given data, you are to calculate a range of descriptive and inferential statistics. Applying and justifying the use of different methods, e.g. histogram, index, correlation, trend forecasting etc.

3. Present your findings in the appropriate format using a range of graphs and charts to communicate data analysis.

4. Be prepared to answer questions related to your analysis and explain all information included on your slides.

Sample Answer

Introduction

In today’s data-driven world, statistics play a central role in effective business management. Every organisation collects data, about its customers, operations, employees, and markets, but without statistical analysis, this information remains meaningless. Statistics turn raw data into insights that guide strategic decisions, improve performance, and reduce uncertainty. In management, statistics help leaders make evidence-based decisions rather than relying on guesswork or assumptions.

Understanding Statistics

Statistics is the science of collecting, organising, analysing, and interpreting data to support decision-making. Its key characteristics include objectivity, quantification, and systematic analysis. Statistical methods can be descriptive, which summarise data, or inferential, which allow predictions and generalisations. For example, analysing last quarter’s sales performance is descriptive, while predicting next quarter’s sales using trends is inferential.

Common statistical methods used in management include correlation analysis, regression, forecasting, and probability analysis. Each of these methods helps managers identify relationships between variables, evaluate risks, and forecast future outcomes based on past trends.

Sources and Types of Business Data

Businesses gather data from both primary and secondary sources.
Primary data are collected directly through surveys, experiments, or observation, and are tailored to the company’s specific needs. Secondary data come from existing sources such as government reports, market research studies, or company databases.

There are also quantitative and qualitative data types. Quantitative data involve numerical values, such as profit margins or sales figures, which are ideal for statistical analysis. Qualitative data capture opinions, attitudes, or behaviours, such as customer satisfaction, which are often interpreted through coding or thematic analysis. Successful organisations combine both data types to form a complete understanding of their business environment.

Sample and Population

In business research, it’s rarely practical to collect data from an entire population, every customer, every sale, or every transaction. Instead, analysts collect data from a sample, a smaller subset that represents the whole. The population refers to the total group under study, while the sample is the portion used for analysis.

For example, Apple might survey 1,000 iPhone users to represent its global customer base. If the sample is chosen carefully, the results can be generalised to the population with a measurable level of confidence. Sampling saves time and cost while still producing reliable insights.

Value of Statistical Methods in Achieving Business Objectives

Statistical management adds measurable value to every business function. It helps organisations identify trends, optimise operations, and assess risk. For instance, Netflix uses predictive analytics to recommend shows based on viewer habits, increasing customer retention. In finance, companies use statistical forecasting to predict cash flows or stock performance.

Statistics also enhance competitive advantage. Firms that understand their data make faster, smarter decisions. Statistical tools reveal which products are profitable, which customers are most loyal, and which marketing campaigns generate the best return on investment. In essence, statistics bridge the gap between data and decision-making.

Continued...