# Quantitative Methods

Bond University

## Course Description

• ### Course Name

Quantitative Methods

• ### Host University

Bond University

• ### Location

Gold Coast, Australia

• ### Area of Study

Mathematics, Statistics

• ### Language Level

Taught In English

• ### Course Level Recommendations

Lower

ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.

### Hours & Credits

• Credit Points

10
• Recommended U.S. Semester Credits
3 - 4
• Recommended U.S. Quarter Units
4.5 - 6
• ### Overview

Introduction
This subject develops mathematical and statistical skills necessary for subsequent quantitative subjects in Actuarial Sciences. The development of the mathematical and statistical foundations includes applications of calculus, probability, discrete and continuous random variables, moment generating functions, sampling distributions, hypothesis testing, application of the central limit theorem to large sample inference and data analytics. The R statistical computing package is used as an integral part of the program.

Learning Objectives
1. Understand different types of data and produce appropriate graphical and numerical descriptive statistics

2. Understand and apply probability rules and concepts relating to discrete and continuous random variables

3. Understand the concept of expectation, variance and moment generating functions for the discrete distributions such as Binomial and Poisson and the continuous distributions such as uniform, exponential and Normal

4. Understand the importance of the Central Limit Theorem (CLT) and its uses and applications; judging appropriate conditions for its application; use the CLT to find probabilities associated with a range of values for a sample average and sample size determination

5. Perform and interpret a variety of hypothesis tests for decision making

6. Develop the basic data analytics skills

7. Use statistical package R most frequently used by practitioners to analyse the data

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