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Level: Level 1 - Undergraduate Introductory Unit 3 2, 4 Faculty of Business, Government & Law School of Management

## Unit Outlines

To view your Unit Outline, click View to log in to MyUC and access this information, or visit your unit's online teaching site.

• Semester 2, 2018, ONLINE, BRUCE (179529) - View
• Semester 2, 2018, ON-CAMPUS, TQB-SB (179530) - View
• Semester 2, 2018, ON-CAMPUS, NSI-SL (179533) - View
• Semester 2, 2018, ON-CAMPUS, BRUCE (179531) - View
• Semester 2, 2017, ONLINE, BRUCE (167757) - View
• Semester 2, 2017, ON-CAMPUS, TQB-SB (167758) - View
• Semester 2, 2017, ON-CAMPUS, NSI-SL (167761) - View
• Semester 2, 2017, ON-CAMPUS, BRUCE (167759) - View
• Flexible and Self Paced Period 10, 2016, SELF-PACED, BRUCE (150108) - View
• Semester 2, 2016, ONLINE, BRUCE (152152) - View
• Semester 2, 2016, ON-CAMPUS, TQB-SB (156505) - View
• Semester 2, 2016, ON-CAMPUS, NSI-SL (155429) - View
• Semester 2, 2016, ON-CAMPUS, BRUCE (155420) - View

## Syllabus

This unit will introduce students to the application of quantitative research methods in the workplace. Students will learn how to apply statistical tools to analyse data, draw conclusions, and make predictions of the future. The unit will begin with data distributions, followed by probability analysis, sampling, hypothesis testing, inferential statistics, and finally, regression. This unit is mathematically intensive, and much of what is learnt here will deal with issues students encounter every day. This unit also makes use of spread sheets, an important tool for working with and making sense of numerical data.

## Learning Outcomes

On successful completion of this unit, students will be able to:

1. Explain the importance of quantitative research methods to business, the differences between quantitative and qualitative data, and identify examples of each type of data;

2. Define and apply the concept of a probability distribution, and explain the properties of different distributions;

3. Differentiate between discrete and continuous probability distributions;

4. Define and apply the concept of a random variable, and differentiate the population from a sample;

5. Describe and identify the different sampling methods, including systematic, stratified random, cluster, convenience, panel, and quota sampling, and identify examples of each;

6. Apply hypothesis testing for testing population parameters using one or two samples;

7. Identify the dependent and independent variables in the linear regression model; and

8. Work with statistical data in a spread sheet environment.

## Contact Hours

150 learning hours in online self-paced mode.

3cp

None

None

## Incompatible Units

8732 Problem Analysis & Statistics OR 5123 Business Statistics

No