NUS
 
ISS
 

Statistics for Business

Overview

Part of -
Duration
Course Time -
Enquiry Please email to iss-blendedlearning@nus.edu.sg

This is an introductory course to help the non-technical users perform a variety of data analysis in order to derive factual insights and ultimately to gain experience in making evidence-based business decisions.

You will explore multiple statistical concepts and learn how to apply them to business use cases. You will work on cleaning and preparing the data for analysis and generating insights. You will experience the use of data visualisation to find answers to business questions. You will learn how to discover correlations in data and to build simple linear regression models. Finally, you will learn about supervised and unsupervised machine learning techniques. Here you will practice building classification trees to predict customer behaviour or condition; and using cluster analysis methods to create customer groupings that would lead to more effective customer management and engagement.

All the topics taught will be delivered through a problem-based approach and active discussions that are driven by use of numerous business scenarios. Emphasis is placed on critical thinking, practice skills and practical knowledge with the use of software and tools only as delivery mechanisms.

Key Takeaways

At the end of the course, learners will be able to:

●  Apply statistics to solve a variety of business problems.

● Compute and interpret data summaries- numerically as well as visually.

● Explore how visual data is used to find answers to business problems.

● Present data visually for better understanding of relationships between variables. 

● Statistically analyse whether there is a relationship between two variables and determine the size of the relationship.

● Predict one variable in terms of another to make improvement in business performance. 

● Perform classification and prediction using decision tree modelling approach.

● Cluster data into homogenous subsets to enable focused group-based customer management. 
 



Structure

●   Course duration: 6 weeks.

●   Learners are recommended to set aside three to four hours of focused learning time to get the most out of the course.

●  This course is designed to be self-paced and cohort-based, with 3 synchronous live sessions via Zoom. Content will be released on a weekly basis.

●   Throughout the course, learners are expected to actively contribute to the group activities and are encouraged to apply the knowledge learnt. They will have ample opportunities to do so via discussions, peer learning, workshops, assessments, and applications.




Live Sessions

Learners are required to attend the mandatory Live Sessions scheduled (via Zoom) as part of the course requirement. This will help to reinforce learning with the cohort.  Please refer to the schedule below for each class:

Class 1
April 2023
●  Live session 1: Mon 13 Mar 2023, 2pm – 3pm *
●  Live session 2: Mon 27 Mar 2023, 2pm – 3pm *
●  Live session 3: Mon 10 Apr 2023, 2pm – 3pm *

* All sessions are in Singapore Time.




Who Should Attend

This course is appropriate for non-technical business professional who aspires to gain practice skills and practical knowledge through hands-on experience in using business analytics to solve real life business problems:

●  Anybody who is just starting to analyse data and need a kick start.

●   Anybody who wants to learn business analytics from the ground up.

●   Anybody who is exploring career opportunities in business analytics.

●   Anybody who is interested to learn how to make data-driven decisions.




Fees And Funding

Type of Learners  Course Fee Total course fee payable, including GST
Learners residing in Singapore (SGD) SGD 900 SGD 963
Learners residing outside Singapore (USD) USD 700 USD 700



Things To Note

● Learners are expected to set aside time for group activities before and beyond the course.

● The NUS-ISS Certificate of Completion will be issued to learners who have met the course requirements successfully. This will include attending all synchronous Zoom sessions and completing the learning activities, workshops and assessments (where applicable).

● Read the terms and conditions of NUS-ISS Course Registration here.

● Read about NUS-ISS and Learner’s Commitment and Responsibilities here.

● All classes are subject to confirmation and NUS-ISS will send an acceptance email to learners one week prior to the commencement date.

● All responses to feedback and surveys conducted by NUS-ISS and its partners must be submitted by learners.




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