Statistics for Business Analytics
Offered By: University of Queensland via edX
Course Description
Overview
Business analytics is the ability to collate and combine multiple streams of data to better understand business processes, customer demands, and relationships between multiple agents.
We live and work in an uncertain world. Every day, business managers, economists, line managers, supervisors and front-line workers must make decisions and predictions based on limited information. This program will help you to make better informed decisions for the future to answer questions like:
- What is the probability that a staff member will need more than 20 days of sick leave in a year?
- Does the new system for preparing food for customers offer a significant improvement over the old system, or is it the same?
- How are sales likely to fluctuate over the next 12 months, based on trends in historical data?
To inform strategic decisions and remain competitive, businesses must leverage the insights contained in the large volumes of data produced both within the business and in the broader business environment. Providing you with skills that are highly sought after in the global workplace, this program will equip you with the analytical know-how needed to extract meaning from complex data sets and translate this meaning into actionable insights.
This program covers a variety of techniques applicable to the collection, presentation, interpretation, and use of numerical data. It provides a foundation for understanding statistical procedures that will help you undertake solid statistical analysis in business and economic situations. This includes statistical inference, probability & sampling distributions, estimation, hypothesis tests, correlation & regression, experimental design, sample survey design, quality sampling, and modern business decision theory.
Syllabus
Course 1: Statistics for Business Analytics: Probability
This is a great course for anyone who wants to gain foundational and critical analysis and statistics skills with no prior background.
In this course, we explore the different ways of determining the probability of different events and outcomes. We want to be able to answer questions like:
- What is the probability that more than 90% of patients will show up for their appointments at a medical practice?
- What are the chances of a store having more than 20 customers in its first two hours of being open?
- How likely is it that a staff member will use 6 or fewer days of sick leave in a year?
Course 2: Statistics for Business Analytics: Samples and Populations
This is a great course for anyone who wants to gain foundational and critical analysis and statistics skills with no prior background.
In this course, we examine the statistical processes of understanding larger populations from smaller samples. We want to be able to answer questions like:
- How large a sample is needed to make a reasonable inference about my customer base?
- What are the upper and lower limits for the percentage of people who wear medium-sized t-shirts in a population?
- Is the income level of native citizens significantly different to that of people born overseas?
Course 3: Statistics for Business Analytics: Modelling and Forecasting
This is a great course for anyone who wants to gain foundational and critical analysis and statistics skills with no prior background.
In this course, we explore statistical methods for examining the relationships between variables. We also consider how data from the past can be used to make forecasts about likely future trends. We want to be able to answer questions like:
- What is the strength of the relationship between quality of customer experience and the likelihood of repeat purchases?
- How accurately can we predict residents’ use of a local park based on their known demographics?
- In what way are sales likely to fluctuate over the next 6 months, based on past data?
Taught by
Temesgen Kifle
Tags
Related Courses
The Data Scientist’s ToolboxJohns Hopkins University via Coursera MARS2014-1x: Metabolic Applied Research Strategy
Ethicon via Independent Experimentation for Improvement
McMaster University via Coursera Molecular Biology - Part 1: DNA Replication and Repair
Massachusetts Institute of Technology via edX Introduction to Linear Models and Matrix Algebra
Harvard University via edX