Statistics Course | SkillsFuture CET Course

Singapore University of Social Sciences

Statistics (BUS105)

Applications Open: 01 October 2024

Applications Close: 15 November 2024

Next Available Intake: January 2025

Course Types: Modular Undergraduate Course

Language: English

Duration: 6 months

Fees: $1392 View More Details on Fees

Area of Interest: Business Administration

Schemes: Alumni Continuing Education (ACE)

Funding: SkillsFuture

School/Department: School of Business

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Synopsis

This course provides students with an understanding of statistical concepts and techniques to generate information for decision-making. The course covers descriptive statistics, probability distributions, sampling distribution, interval estimation, hypothesis testing, ANOVA and regression. Emphasis will be placed on acquiring the analytical and interpretative skills needed to understand statistical findings.

Level: 1
Credit Units: 5
Presentation Pattern: EVERY REGULAR SEMESTER

Topics

Describing Data: Frequency Tables, Frequency Distributions and Graphic Presentation.
Describing Data: Numerical Measures
Discrete Probability Distributions
Continuous Probability Distributions
Sampling Methods
Central Limit Theorem
Point Estimate
Confidence Intervals for Population Mean
Confidence Intervals for Population Proportion
Finite-Population Correction Factor
Choosing an Appropriate Sample Size
One-Sample Test of Hypothesis
Two-Sample Test of Hypothesis
Comparing Two Population Variances
Comparing Multiple Population Means
Correlation Analysis
Simple Linear Regression Analysis
Multiple Regression Analysis

Learning Outcome

Describe statistical data.
Define probability, mean and standard deviations for a probability distribution.
Explain the probabilities for sample mean and proportion.
Identify Confidence Interval for the mean and proportion of a population.
Execute the Hypothesis Testing (both one-sample and two-samples) for the population mean and proportion population.
Apply an Analysis of Variance (ANOVA) procedure to compare the means of independent random samples.
Implement and fit a Linear Regression Line to a set of sample data and interpret the results.
Interpret the results from Multiple Regression Analyses.
Use a suitable computer software to perform data analyses according to the statistical concepts and techniques learnt from this course including data summary and presentation, probability computation, confidence intervals, hypothesis tests and linear and multiple regression analyses.
Report and explain the outcome of a particular statistical analysis performed for decision-making.
Summarise statistical analyses and findings through oral presentations in class or on recorded video.
Demonstrate the essential knowledge and interpersonal skills to work effectively in a team.
Show well-developed written proficiency in statistical report.