This course introduces students to the science of business analytics while casting a keen eye toward the artful use of numbers found in the digital space. The goal is to provide businesses and managers with the foundation needed to apply data analytics to real-world challenges they confront daily in their professional lives.
Students will learn to identify the ideal analytic tool for their specific needs; understand valid and reliable ways to collect, analyze, and visualize data; and utilize data in decision making for their agencies, organizations or clients.
Syllabus
WEEK 1
Course Introduction
With the first module, we will measure and identify satisfied customers to adjust product or service accordingly. To measure the customer satisfaction we will measure expectations, performance and disconfirmation of the offered product or service. We will also provide an overview of marketing analytics used to gauge the effectiveness of different marketing activities. Finally, we will go through measurement and scaling techniques.
WEEK 2
We will explore the marketing world through process of A/B testing, design of experiments, data analysis, and hypothesis testing. Next, we study Analysis of Variance (ANOVA) which is used to determine significant differences between two or more categorical groups. We will study ANOVA’s assumptions, test inference and different types of ANOVA. We also spend some time in designing experiments.
WEEK 3
We will learn about the Binary Outcome model using Logit function. Logistic regression is used when the dependent variable has a binary outcome. We will also review linear regression, which is used when the dependent variable has a continuous outcome.
WEEK 4
We will learn an introduction to text analytics for marketing and how we can use tools, such as the Social Media Macroscope, to find insights about consumer responses within the realm of marketing .
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