Inferential and Predictive Statistics for Business

Go to Course: https://www.coursera.org/learn/business-statistics

Introduction

### Course Review: Inferential and Predictive Statistics for Business on Coursera **Overview:** "Inferential and Predictive Statistics for Business" is an exceptional course offered on Coursera that provides a solid foundation in statistical methods indispensable for effective business decision-making. As organizations face increasingly complex data landscapes, mastering these concepts is not just beneficial but essential. This course equips students with the analytical tools required to unravel uncertainties inherent in business processes, fostering a structured approach to problem-solving. **Course Highlights:** The course is divided into strategically designed modules, each targeting specific aspects of inferential and predictive statistics. Key takeaways from each segment include: 1. **Course Orientation:** The first module serves as an introduction to the course structure, emphasizing the importance of collaboration among peers and ensuring that learners are equipped with the necessary technical knowledge for navigating the course effectively. 2. **Module 1: Hypothesis Testing:** This module dives into the critical concept of hypothesis testing, demonstrating how it underpins the evaluation of claims often encountered in marketing and product promotions. By learning the principles of testing, students gain the capability to discern fact from exaggeration, which is vital for sound business practices. 3. **Module 2: Statistical Inference Based on Two Samples:** Here, learners explore the methods of comparing two groups, such as the effectiveness of different treatments or products. The insights gained from this module aid managers in making data-driven decisions about product efficacy, ensuring that claims are supported by statistics. 4. **Module 3: Simple Linear Regression:** This segment discusses the relationship between variables, illustrated through a famous study of London bus drivers. Understanding linear regression not only allows students to identify correlations but also to make predictions based on historical data, which is invaluable in forecasting outcomes based on specific variables. 5. **Module 4: Multiple Linear Regression:** As students grapple with the complexities of multiple influencing factors on business outcomes, this module stands out by introducing multiple linear regression. This statistical tool helps in untangling the various elements affecting sales or operational performance, moving beyond anecdotal evidence to insights grounded in data. **Why You Should Enroll:** The course is meticulously structured, ensuring that even those without a strong statistical background can grasp fundamental concepts. The real-world applications of statistical methods discussed in this course make it particularly relevant for managers and decision-makers. By the end of the course, you will have the competence to assess variabilities around you, create predictive models, and make informed decisions that enhance your business's performance. **Conclusion and Recommendation:** If you're in a managerial role or aspire to take on such responsibilities, "Inferential and Predictive Statistics for Business" on Coursera is an invaluable resource. It bridges the gap between abstract statistical theories and practical business applications, empowering you to navigate uncertainty effectively. I highly recommend this course to anyone looking to bolster their analytical capabilities. It will not only enrich your toolkit but also enhance your confidence in making data-driven decisions that can lead to substantial improvements in your business strategies. Enroll today, and take the first step toward mastering the art of predictive analytics!

Syllabus

Course Orientation

In the course orientation, you will become familiar with the course, your classmates, and our learning environment. The orientation will also help you obtain the technical skills required for the course.

Watch any infomercial and you hear many outrageous promises. Use this cream and your skin will look 80% firmer! Use this supplement and you will lose 10 pounds in the first 10 days! Are they telling you the truth? Are they all lying? The only way to know the answer to any of these questions is to scientifically test the claim being made – that is what we call hypothesis testing and what we will learn in this module.

Does the medicine a person is taking to treat his condition really work better than a sugar pill? Is the new chip-enabled credit card more secure than the magnetic card? How do you know whether the claims being made about anything being “better than” or “faster than” a competitor are true? In this module we will learn to make this comparison.

Does your job involve a lot of sitting? If so, you are at higher risk of coronary heart disease. How do I know this? We got to know the relationship between coronary heart disease and sitting when researchers studied a cohort of London bus drivers and bus conductors from 1947 to 1972. If you want to know more, then read on!

You are trying to predict next month’s sales numbers. You know that dozens, maybe even hundreds, of things like the weather, competitor’s promotions, rumors, etc. can impact the number. You talk to five people and each one has an idea about what makes the biggest impact, and the only thing they offer is “trust me.” Do you wish there was a better way of doing this rather than relying on blind faith? Well, there is. We can use Multiple Regression to sort through this mess and bring the focus to factors that really do matter.