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WSQ - Statistics Fundamental Training for Beginners

WSQ - Statistics Fundamental Training for Beginners

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Embark on your journey into the world of statistics with our WSQ-endorsed Statistics Fundamental Training for Beginners course. This comprehensive training covers essential statistical concepts, including data collection, types of data, basic probability, and data interpretation methods. Through real-world examples and hands-on exercises, you'll gain the skills needed to understand, analyze, and interpret data in various contexts.

By the end of this course, you'll possess a strong foundational understanding of basic statistics. You’ll be equipped to tackle data with confidence, understand statistical tests, and make informed decisions based on your analyses. Whether you're entering the workforce, looking to upskill, or just interested in the power of data, this course serves as an excellent stepping stone into the world of statistics.

Course Objective

Learners will be able to perform statistical analysis with analytics tools

Course Learning Outcomes

After the end of this course, learners will be able to

LO1: Apply descriptive statistics and probability theory to describe data
LO2: Apply sampling theory to estimate population statistics and confidence interval
LO3: Perform hypothesis testing for means and proportions
LO4: Perform goodness of fit testing
LO5: Perform analysis of variance testing
LO6: Perform regression statistical modeling
LO7: Determine correlation and covariance among multiple factors

Course Brochure

Download WSQ - Statistics Fundamental Training for Beginners Brochure

Skills Framework

This course follows the guideline of Data and Statistical Analytics PTP-BIN-4055-1.1 TSC under Public Transport Skills Framework

Certification

Certificate of Completion from Tertiary Infotech - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Completion from Tertiary Infotech.
OpenCerts from SkillsFuture Singapore - After passing the assessment(s) and achieving at least 75% attendance, participants will receive a OpenCert (aka Statement of Achievement) from SkillsFuture Singapore, certifying that they have achieved the Competency Standard(s) in the above Skills Framework.

WSQ Funding

WSQ funding is only applicable to Singaporeans and PR. Subject to eligibility, the funding support is subjected to funding caps.

Effective for courses starting from 1 Jan 2024
Full Fee	GST	Nett Fee after Funding (Incl. GST)
		Baseline	MCES / SME
$750.00	$67.50	$442.50	$292.50

Baseline: Singaporean/PR age 21 and above
MCES(Mid-Career Enhanced Subsidy): S'porean age 40 & above

Upon registration, we will advise further on how to tap on the WSQ Training Subsidy.

You can pay the nett fee (after the WSQ training subsidy) by the following :

SkillsFuture Enterprise Credit (SFEC)

Eligible Singapore-registered companies can tap on $10000 SFEC to cover out-of-pocket expenses.Click here to submit SkillsFuture Enterprise Credit

SkillsFuture Credit (SFC)

Eligible Singapore Citizens can use their SFC to offset course fee payable after funding but the $4,000 Additional SFC (Mid-Career Support) cannot be used. Click here for SkillsFuture Credit submission

UTAP

Eligible NTUC members can apply for 50% of the unfunded fee from UTAP, capped up to $250/year and for members aged 40 and above, capped up to $500/year. Click here to submit UTAP

PSEA

Eligible Singapore Citizens can use their PSEA funds to offset course fee payable after funding. Please inform us if you intend to use your PSEA funding.

To check for Post-Secondary Education Account (PSEA) eligibility for this course, Visit SkillsFuture (course code: TGS-2020504142)

Scroll down to “Keyword Tags” to verify for PSEA eligibility.
If there is “PSEA” under keyword tags, the course is eligible for PSEA.

Once you are eligible for PSEA, please download and fill up the PSEA Withdrawal Form and email to us.

Course Code: TGS-2020504142

Post-Course Support

We provide free consultation related to the subject matter after the course.
Please email your queries to enquiry@tertiaryinfotech.com and we will forward your queries to the subject matter experts.

Course Cancellation/Reschedule Policy

You can register your interest without upfront payment. There is no penalty for withdrawal of the course before the class commerce.
We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% for any paid amount.
Note the venue of the training is subject to changes due to availability of the classroom

Course Details

Topic 1: Introduction to Statistics

Why Statistics Matter
Categorical and Quantitative Data
Descriptive Statistics: Mean and Standard Deviation
Probability and Conditional Probability
Bayes Theorem
Discrete Probability Distributions
Continuous Probability Distributions
Software for Statistical Analysis

Topic 2: Sampling

Sampling Consideration
Central Limit Theorem
Sampling Distribution of the Mean
Standard Errors for Proportion and Mean
Confidence Interval
T-Statistics vs Z-Statistics
T-Score Table and Degree of Freedom
Calculating Confidence Interval of T-Score

Topic 3: Hypothesis Testing

Overview of Hypothesis Testing
Steps for Performing a Hypothesis Testing
One Tailed vs Two Tailed Hypothesis Testing
One Sample Hypothesis Testing
Two Sample Hypothesis Testing
Pooled Sample T-Test
Type 1 and Type 2 Errors

Topic 4: Chi Square Test

Chi Square Distribution
Goodness of Fit Test

Topic 5: ANOVA: Analysis of Variance

What is Analysis of Variance
One Way ANOVA
Total Sum of Squares
Within Variance and Between Variance (SSW and SSB)
Hypothesis Testing with F-Statistic

Topic 6: Regression

What is Regression?
Residues and Mean Square Error
Perform Regression Modeling

Topic 7: Correlation Analysis

What is Correlation Analysis?
Computation of Correlation Coefficient
Correlation and Covariance Matrices

Final Assessment

Written Assessment - Short Answer Questions (WA-SAQ)
Practical Performance (PP)

Course Info

Promotion Code

Promo or discount cannot be applied to WSQ courses

Minimum Entry Requirement

Knowledge and Skills

Able to operate using computer functions with minimum Computer Literacy Level 2 based on ICAS Computer Skills Assessment Framework
Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)

Attitude

Positive Learning Attitude
Enthusiastic Learner

Experience

Minimum of 1 year of working experience.
Minimum 18 years old

Minimum Software/Hardware Requirement

Software:

You can download and install the following software:

Hardware: Windows and Mac Laptops

About Progressive Wage Model (PWM)

The Progressive Wage Model (PWM) helps to increase wages of workers through upgrading skills and improving productivity.

Employers must ensure that their Singapore citizen and PR workers meet the PWM training requirements of attaining at least 1 Workforce Skills Qualification (WSQ) Statement of Attainment, out of the list of approved WSQ training modules.

For more information on PWM, please visit MOM site.

Funding Eligility Criteria

Individual Sponsored Trainee

Employer Sponsored Trainee

Singapore Citizens or Singapore Permanent Residents of age 21 and above
From 1 October 2023, attendance-taking for SkillsFuture Singapore's (SSG) funded courses must be done digitally via the Singpass App. This applies to both physical and synchronous e-learning courses.
Trainee must pass all prescribed tests / assessments and attain 100% competency.
We reserves the right to claw back the funded amount from trainee if he/she did not meet the eligibility criteria.

Singapore Citizens or Singapore Permanent Residents who are DIRECT EMPLOYEE of the sponsoring company.
From 1 October 2023, attendance-taking for SkillsFuture Singapore's (SSG) funded courses must be done digitally via the Singpass App. This applies to both physical and synchronous e-learning courses.
Trainee must pass all prescribed tests / assessments and attain 100% competency.
We reserves the right to claw back the funded amount from the employer if trainee did not meet the eligibility criteria.

SkillsFuture Credit:

Eligible Singapore Citizens can use their SkillsFuture Credit to offset course fee payable after funding.

PSEA:

To check for Post-Secondary Education Account (PSEA) eligibility, goto mySkillsFuture portal and search for this course code.
Scroll down to "Keyword Tags" to verify for PSEA eligibility.
If there is “PSEA” under keyword tags, the course is eligible for PSEA.
And if there is no “PSEA” under keyword tags, the course is ineligible for PSEA.
Not all courses are eligible for PSEA funding.

Absentee Payroll (AP) Funding:

$4.50 per hour, capped at $100,000 per enterprise per calendar year.
AP funding will be computed based on the actual number of training hours attended by the trainee.

SFEC:

If the Training Provider has submitted an enrolment for course fee grant claim in Training Partners Gateway (TPGateway), SSG would be able to derive SFEC funding based on this record. There is no need for enterprise to submit any claim request and the SFEC claim will be automatically generated and disbursed.
Where there is no such record, eligible employers are required to submit an SFEC claim after course completion via the SFEC microsite.
SkillsFuture Enterprise Credit (SFEC) Microsite

Steps to Apply Skills Future Claim

The staff will send you an invoice with the fee breakdown.
Login to the MySkillsFuture portal, select the course you’re enrolling on and enter the course date and schedule.
Enter the course fee payable by you (including GST) and enter the amount of credit to claim.
Upload your invoice and click ‘Submit’

SkillsFuture Level-Up Program

The SkillsFuture Level-Up Programme provides greater structural support for mid-career Singaporeans aged 40 years and above to pursue a substantive skills reboot and stay relevant in a changing economy. For more information, visit SkillsFuture Level-Up Programme

Get Additional Course Fee Support Up to $500 under UTAP

The Union Training Assistance Programme (UTAP) is a training benefit provided to NTUC Union Members with an objective of encouraging them to upgrade with skills training. It is provided to minimize the training cost. If you are a NTUC Union Member then you can get 50% funding (capped at $500 per year) under Union Training Assistance Programme (UTAP).

For more information visit NTUC U Portal – Union Training Assistance Program (UTAP)

Steps to Apply UTAP

Note

SSG subsidy is available for Singapore Citizens, Permanent Residents, and Corporates.
All Singaporeans aged 25 and above can use their SkillsFuture Credit to pay. For more details, visit www.skillsfuture.gov.sg/credit
An unfunded course fee can be claimed via SkillsFuture Credit or paid in cash.
UTAP funding for NTUC Union Members is capped at $250 for 39 years and below and at $500 for 40 years and above.
UTAP support amount will be paid to training provider first and claimed after end of class by learner.

Appeal Process

The candidate has the right to disagree with the assessment decision made by the assessor.
When giving feedback to the candidate, the assessor must check with the candidate if he agrees with the assessment outcome.
If the candidate agrees with the assessment outcome, the assessor & the candidate must sign the Assessment Summary Record.
If the candidate disagrees with the assessment outcome, he/she should not sign in the Assessment Summary Record.
If the candidate intends to appeal the decision, he/she should first discuss the matter with the assessor/assessment manager.
If the candidate is still not satisfied with the decision, the candidate must notify the assessor of the decision to appeal. The assessor will reflect the candidate’s intention in the Feedback Section of the Assessment Summary Record.
The assessor will notify the assessor manager about the candidate’s intention to lodge an appeal.
The candidate must lodge the appeal within 7 days, giving reasons for appeal
The assessor can help the candidate with writing and lodging the appeal.
he assessment manager will collect information from the candidate & assessor and give a final decision.
A record of the appeal and any subsequent actions and findings will be made.
An Assessment Appeal Panel will be formed to review and give a decision.
The outcome of the appeal will be made known to the candidate within 2 weeks from the date the appeal was lodged.
The decision of the Assessment Appeal Panel is final and no further appeal will be entertained.
Please click the link below to fill up the Candidates Appeal Form.

Job Roles

Data Analyst
Market Researcher
Business Analyst
Quality Assurance Specialist
Social Science Researcher
Graduate Student
Economic Analyst
Product Manager
Human Resources Analyst
Healthcare Data Specialist
Educational Researcher
Sports Statistician
Financial Analyst
Behavioral Scientist
Environmental Data Specialist.

Trainers

Dr Alvin Ang – Dr Alvin Ang is an ACLP-certified trainer with a Ph.D. in Operations Research from Nanyang Technological University and more than a decade of teaching and research experience. He has taught statistics, quantitative methods, and data analytics at NTU, SUSS, Curtin University, and SP Jain School of Global Management, earning multiple teaching awards. He also brings practical experience as a data science consultant and founder of DataFrens.sg, an open-source data science community.

Dr Ang’s training in statistics fundamentals is designed to make abstract concepts approachable for beginners. He introduces learners to key topics such as probability, sampling, hypothesis testing, and regression, using Python, R, and Excel-based methods. With his engaging and learner-centered approach, Dr Ang ensures participants develop not only technical skills but also the ability to interpret and communicate statistical insights effectively in business and research contexts.

Ken Hiong – Ken Hiong is an ACLP-certified trainer with more than 15 years of experience in business analytics, financial planning, and statistical modeling. He has held key roles at Pfizer, Pharmacia, and SciGen, supporting regional business development with data-driven forecasting, variance analysis, and financial modeling. Currently an associate trainer with Tertiary Courses, Ken delivers courses in Excel, Power BI, SQL, and statistical tools, specializing in helping learners apply quantitative techniques to solve business problems.

In his statistics training, Ken emphasizes practical applications of statistical methods for decision-making. His courses introduce learners to descriptive statistics, probability distributions, and hypothesis testing, with hands-on exercises in Excel and Python. By blending his corporate analytics background with teaching expertise, Ken ensures participants acquire the skills to apply statistics confidently in both professional and academic settings.

Liew Sing Loon – Liew Sing Loon is an ACLP-certified trainer with a strong background in adult education and applied learning. With years of experience designing and delivering WSQ-aligned programs, he specializes in making complex technical concepts accessible to learners from diverse professional backgrounds. His expertise includes quantitative reasoning, data literacy, and statistical tools for business applications.

In his statistics fundamentals training, Liew focuses on building a clear conceptual foundation for beginners. He guides learners through core topics such as measures of central tendency, variability, probability, and statistical inference, ensuring they gain both theoretical understanding and practical skills. With his learner-centered teaching style and structured approach, Liew equips participants to apply statistics effectively in workplace scenarios and decision-making processes.

Dwight Nuwan Fonseka – Dwight Nuwan Fonseka is an ACLP-certified trainer and Head of Data Science at Plano Pte. Ltd., where he leads projects in predictive modeling, big data, and statistical analytics. He also serves as an adjunct lecturer at the London School of Business and Finance, coordinating the Diploma in Data Analytics program, and as an associate trainer with Tertiary Courses. His expertise spans R, Python, Tableau, and advanced statistical modeling techniques including regression, ANOVA, and hypothesis testing.

In his training, Dwight emphasizes hands-on learning, guiding learners from the basics of descriptive and inferential statistics through to applications in data-driven decision-making. His structured approach ensures that beginners not only grasp statistical concepts but also gain the confidence to apply techniques such as t-tests, correlation, and simple regression to real-world datasets. By integrating practical exercises with theory, Dwight empowers learners to build a strong statistical foundation for further studies in analytics and data science.