Quantitative Data Reasoning Bootcamp



Course Reference Number:
CRS-N-0053437 (Classroom Learning)
CRS-N-0051991 (Synchronous e-Learning)

Courses_Calendar_83x95

Course Objectives

In this age of Big Data, how do we make sense of the abundance of readily accessible but often overwhelming quantitative information encountered at work? How do we go about systematically extracting insights from data? What does it mean to reason with data? Quantitative data reasoning can be thought of as applying a certain set of logic that allows us to work with data. In applying this logic, we make use of statistical methods and other forms of numerical analysis to answer questions that we are invested in, support or invalidate preconceived hypotheses and provide evidence to advance our arguments. The course's primary objective, therefore, is to develop the relevant skills that will allow us to apply this logic, so that we may effectively utilize data as a valuable resource to help inform and guide decision-making.  

The course aims to impart quantitative data reasoning skills. These broadly encompass the ability to ask good questions; curate and organize datasets; visualize data; perform mathematical processing; carry out an analysis (eg. using models) with clear assumptions; and to communicate the results effectively.    

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

  • Understand and articulate the logic that undergirds quantitative analyses.
  • Demonstrate how this logic can be applicable to questions in their own professions.
  • Become critical consumers of quantitative knowledge.
  • Actively use data in a thoughtful, critical and reflective manner.

Outline

Day 1

  • The logic of reasoning quantitatively with data
  • Hypothesis formulation, operationalising constructs
  • Data collection and cleaning
  • Use of descriptive statistics and data visualisation methods; when to use what in which situations

Day 2

  • The role of probability in reasoning with data
  • Statistical inference – drawing conclusions from our data
  • Using models – how to mathematically represent relationships in our data
  • How to effectively communicate our results

Tools

Orange, RStudio

Pre-requisites

Anyone who is interested in using data more effectively in their work processes  

Who Should Attend

Managers, Executives, Engineers

Mode of Training

On-campus or Online (Live)

Speaker

Dr. Edmund Low

 

Edmund Low is a lecturer with the University Scholars Programme (USP) at the National University of Singapore. He has more than 14 years of academic and professional experience in the use of data-driven tools to answer questions in public health and the environment. His past projects include the use of programming and visual libraries to develop simulation models for automating workflow processes, and the setting up of remote environmental sensing systems to automate real-time continuous monitoring, for early incident warning. He currently heads the quantitative reasoning domain, and is also director of the Quantitative Reasoning Centre, at USP. As an educator, Edmund has received both the USP Teaching Excellence Award, as well as the NUS Annual Teaching Excellence Award. Edmund holds a PhD in Environmental Engineering from Yale University.

DATE

10 - 11 Dec 2020 (Online)

DURATION

2 Days
9.00am – 5.30pm

VENUE

National University of Singapore
University Town

International Participants

S$1,819.00

Incl. GST

Singapore Citizens
(39 yrs old or younger) 

or 

Singapore PRs

S$545.70

Incl. GST

Singapore Citizens
(40 yrs or older)

S$205.70

Incl. GST

Enhanced Training Support for SMEs

S$205.70

Incl. GST

Sign Up Now


Fees & Fundings

International
Participant
Singapore Citizen1
39 years old or younger
Singapore Citizen1
40 years or older eligible for MCES2
Singapore PRs Enhanced Training
Support for SMEs3
Full Programme Fee S$1,700.00 S$1,700.00 S$1,700.00 S$1,700.00 S$1,700.00
SkillsFuture Funding
(Refer to Funding Page for Claim Period)
- (S$1,190.00) (S$1,190.00) (S$1,190.00) (S$1,190.00)
Nett Programme Fee S$1,700.00 S$510.00 S$510.00 S$510.00 S$510.00
7% GST on Nett
Programme Fee
S$119.00 S$35.70 S$35.70 S$35.70 S$35.70
Total Nett Programme
Fee Payable, Incl. GST
S$1,819.00 S$545.70 S$545.70 S$545.70 S$545.70
Less Additional Funding if
Eligible Under Various Scheme
- - (S$340.00) - (S$340.00)
Total Nett Programme Fee, Incl. GST,
after additional funding from the various funding schemes
S$1,819.00 S$545.70 S$205.70 S$545.70
S$205.70


  1. All self-sponsored Singaporeans aged 25 and above can use their $500 SkillsFuture Credit to pay for the programme. Visit http://www.skillsfuture.sg/credit to select the programme. 
  2. Mid-Career Enhanced Subsidy (MCES) - Singaporeans aged 40 and above may enjoy subsidies up to 90% of the programme fee. 
  3. Enhanced Training Support for SMEs (ETSS) - SME-sponsored employees (Singaporean Citizens and PRs) may enjoy subsidies up to 90% of the programme fee. For more information, visit http://www.ssg.gov.sg/programmes-and-initiatives/training/enhanced-training-support-for-smes.html?_ga=2.154478072.1748789781.1519700056-512306731.1519700056
  4. Eligible organisations (excluding government entities) may apply for the absentee payroll funding via SkillsConnect at www.skillsconnect.gov.sg for Singaporean/permanent resident participants attending the programme during working hours. The absentee payroll funding is computed at 80% of hourly basic salary capped at $4.50 per hour or $7.50 per hour for SME. For more information, visit https://www.skillsconnect.gov.sg/sop/portal/e-Services/For%20Employers/AbsenteePayroll.jsp
  5. Eligible individuals may apply for training allowance capped at $6/hr under the WSS scheme, visit- https://www.wsg.gov.sg/programmes-and-initiatives/workfare-skills-support-scheme-individuals.html for more information on WSS.
  6. NTUC Training Fund (SEPs) – All self-employed (i.e. freelancers and sole-proprietors-with-no-employee) Singaporeans and Permanent Residents are eligible to apply for the NTUC Training Fund (SEPs) from NTUC’s Employment and Employability Institute (e2i). Click here for more information.
Sign Up Now
 
20 November 2020