Business Statistics Master's Programs

Students who would like to have a career in the field of business analytics, data analytics, or commercial insights management should consider earning a degree in business analytics with a focus on business statistics. Schools offering Business Intelligence degrees can also be found in these popular choices.

Degree Information for Business Statistics Master's Programs

Students who want to learn how to utilize large-scale consumer data for the purpose of improving business strategies should consider enrolling in a two-year business analytics master's program with a focus on business statistics. Applicants must have completed a four-year bachelor's degree with a focus on business or have at least one year's work experience in the field of business.

Some courses that students might have to take in order to earn this degree include managerial statistics, market structure and firm strategy, and advanced statistical modeling for business.

Market Structure and Firm Strategy

Industry organization and interfirm rivalry in the contemporary market environment will be examined by students taking this course. The nature and degree of competition in any given industry is determined with the help of microeconomic tools developed in class by the students. The economic models of firm behavior and market structure are presented and discussed in class in order to explain and evaluate industry performance. Merger activities, scale economics, cartelization, and entry barriers are used to analyze market definition.

Managerial Statistics

The fundamental statistical techniques used in a managerial setting will be covered in this course. Conceptual exercises and case studies are used by students to understand the applicability of statistical methods in managerial roles. The effective use of graphical and numerical summaries, hypothesis testing and regression, and estimation and confidence intervals are some of the statistical topics that will be studied in class. Class projects might include more advanced topics such as the principles of model building and data mining.

Equity Valuation

Students taking this course will learn to use the top-down approach, along with industry forecasting and analysis, to value equity securities. The course examines the models and application of valuation theory. Students gain an in-depth understanding of the workings of the equity market by analyzing IPO processes. Where these markets are headed and the issues that affect them are also examined in detail. The financial statements on risk and cash flow, valuing bankrupt and distressed companies, and venture capital situations are some of the more advanced topics covered in this course.

Statistical Modeling for Business

The statistical modeling situations reliant on numerous variables that are commonly found in a plethora of business applications are studied in this course. Cluster analysis, logistics regression, decision trees, and factor analysis are some of the topics that are typically examined in class. Customer segmentation, market analytics, finance and health analytics, and direct mail response are some of the major applications of these statistical modeling methodologies in the business world.

Enterprise Risk Analytics

The major current and emerging approaches in the domain of enterprise risk analytics, used by government organizations and corporations, are studied in this course. In class, emphasis will be laid on understanding and implementing the framework for enterprise risk management, which enables managers to increase company value by leveraging opportunities around the firm. The major risk categories, such as operational, financial, and strategic risk factors, are discussed in class. For each of these risks, the appropriate risk analytics approach will be examined.

Computational Statistics

In this course, students will learn efficient methods for solving statistically formulated problems. A range of computationally intensive statistical techniques will be discussed in class and the role of computation as a means of discovery will be studied. Numerical optimization in statistical inference, randomization methods, and the tools for the identification of structure in data are some of the topics that will be covered. Analyzing, understanding, and applying complex data in corporate processes, as well as using statistical computing methods, will be focused on and emphasized.

Data Mining and Statistical Learning

The computational tools used for the purpose of understanding large and complex data sets will be analyzed in this course. Building models that can use a collection of inputs to predict a qualitative or quantitative output will be emphasized. The use of data to understand the assumptions, motivations, and methodologies that drive the market is taught in class.

Business Statistics Master's Programs: Admission Prerequisites

Students seeking enrollment in a business analytics master's program with a focus on business statistics should submit the following documents along with their application form:

  • Personal statement in essay format
  • Professional or academic references
  • Transcripts from all institutions previously attended
  • Current CV or resume
  • GRE and GMAT scores

In conclusion, students who have completed a business-focused bachelor's degree program or have at least a year's work experience may apply for a business analytics master's program focusing on business statistics. To earn this degree, the student might need to take courses such as managerial statistics, enterprise risk analytics, and equity valuation.

To continue researching, browse degree options below for course curriculum, prerequisites and financial aid information. Or, learn more about the subject by reading the related articles below:

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