Most MBA programs include a statistics or quantitative analysis course. In Emporia State University's online MBA program, the course is titled Quantitative Analysis of Business Decisions. It is one of the most valuable courses for future business managers and executives. This course introduces the student to quantitative approaches in business decision-making. Methods include decision analysis, regression analysis in forecasting, as well as linear and integer programming to solve transportation, project scheduling, inventory management, multi-criteria decision problems, and others.
What Is Statistics or Quantitative Analysis?
Quantitative analysis uses mathematical and statistical modeling, measurement, and research to provide insight into past, current and future events. Any subject involving numbers can be quantified, and the concepts involved in statistics or quantitative analysis can prove useful, including subjects as wide ranging as social science, chemistry, sports, and financial analysis. In business, quantitative analysis is commonly used to analyze return on assets, sales revenues, profit margins, process control and customer surveys.
The methods of quantitative analysis taught in this course provide predictive capabilities and the capacity to derive insights from data that drive strategic decision-making. These skills are useful in applications across business functions, and in being able to collaborate with and understand the number crunchers or quants who will help to inform your future business decision-making.
How Quantitative Analysis Differs from Qualitative Analysis
These two disciplines combine to give business executives a complete set of analysis tools. Qualitative analysis evaluates information that cannot easily be reduced to numeric values, such as employer reputation or employee morale. Whereas qualitative analysis seeks to find meaning and insight into human behavior, quantitative analysis helps extract patterns and explore relationships among two phenomena or quantify business activities.
Key Concepts in Quantitative Analysis
Several factors contribute to the validity of findings in quantitative analysis. Proficiency in the methods you will learn in this program requires a mastery of these fundamental factors or concepts:
- Validity: This is the extent to which what you think you are measuring actually corresponds to what you are measuring in the real world. For example, you may conduct a survey about brand loyalty, but if the questions do not help customers reveal the extent to which they would repurchase or recommend your products, the survey results will prove invalid.
- Reliability: This concept is the measure of the consistency of a method or a metric for reaching objective conclusions. If a method produces inconsistent results, such that findings are not always true, it is an unreliable method. There are common ways of testing for reliability, including test-retest, which aims to establish identical results when the same test is performed with the same conditions.
- Statistical Significance: This concept addresses the issue of randomness and sampling errors or margins of error. This shows that the observable difference is not likely due to sampling error alone.
- Experimental Validity: Derived from the scientific method, experimental validity requires managing confounding variables and minimizing the effects of bias.
- Correlations: Used to measure the strength of a relationship between variables, correlation does not imply causation. Strongly correlated variables will appear to move together, reliably over time, given the same conditions.
Developing your quantitative skills will improve business decision-making and increase positive outcomes in all of your future business endeavors.
Learn more about Emporia State University's online MBA program.
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