35151 Introduction to Statistics
Warning: The information on this page is indicative. The subject outline for a particular semester, location and mode of offering is the authoritative source of all information about the subject for that offering. Required texts, recommended texts and references in particular are likely to change. Students will be provided with a subject outline once they enrol in the subject.
UTS: Science: Mathematical SciencesCredit points: 6 cp
Result type: Grade and marks
Anti-requisite(s): 33116 Statistical Design and Analysis AND 33230 Mathematical Modelling 2 AND 33290 Statistics and Mathematics for Science
Handbook description
Statistics is the science of collecting, organising and interpreting data. These data may come from designed experiments, may be collected in a questionnaire or may be the result of market activity, but many of the statistical techniques are independent of the source of the data and some of them are introduced in this subject. After a general introduction, some of the common distributions and their usefulness in data summary are presented. Formal tests about the mean and variance are developed and then a number of standard techniques from regression, designed experiments and quality control are introduced.
Subject objectives/outcomes
At the completion of this subject students are expected to be able to:
- demonstrate an understanding of basic statistical concepts
- explain the meaning of statistical terms that commonly occur in reports and articles
- carry out an investigation of a set of data using summary statistics, graphs and techniques of exploratory data analysis
- make inferences from sample data to populations
- state the assumptions underlying the use of particular statistical techniques and check whether they are satisfied
- use a statistical computer package and interpret its output
- communicate clearly the results of a statistical analysis.
Contribution to course aims and graduate attributes
This subject will contribute to the recognition of your attainment of the following Faculty of Science graduate attributes:
1. Disciplinary knowledge and its appropriate application
2. An inquiry-oriented approach
3. Professional skills and their appropriate application
4. Communication skills
5. Initiative and innovative ability
Teaching and learning strategies
Two 1.5-hour lectures and one 2-hour computer laboratory per week. Outside of lectures and laboratories, you will need to spend at least six hours per week of individual or group study.
Content
This subject will cover topics selected from: descriptive statistics, normal distributions, relations in categorical data, design of experiments and sampling, probability and random variables, sampling distributions of proportion and mean, estimation and confidence intervals, hypothesis tests, simple and multiple linear regression, one way and two way ANOVA and statistics for quality.
Assessment
Assessment Item 1: Laboratory worksheets
Objective(s): | subject objects a) to g) |
Weighting: | 10% |
Criteria: | Correct use of terminology; correct choice and use of problem solving strategies and procedures |
Assessment Item 2: Two Assignments
Objective(s): | subject objects a), b) and d) to g) |
Weighting: | 30% |
Criteria: | Correct use of terminology; correct choice and use of problem solving strategies and procedures; presentation in required format; careful reasoning |
Assessment Item 3: Examination
Objective(s): | subject objects a) to g) |
Weighting: | 60% |
Criteria: | Correct use of terminology; correct choice and use of problem solving strategies and procedures; careful reasoning |
Minimum requirements
Student must obtain at least 40% of the marks available for the final examination in order to pass this subject. If 40% is not reached, an X grade fail may be awarded for the subject, irrespective of an overall mark greater than 50.
Students should demonstrate competence in all aspects of the assessment in order to pass the subject. To pass the subject, a student must achieve a final result of 50% or more. The final result is simply the sum of all the marks gained in each piece of assessment.
Recommended texts
Peck, R., Olsen, C. and Devore, J. Introduction to Statistics & Data Analysis, 4th ed., Cengage, 2012.
References
Moore, D. S. and McCabe, G. P. Introduction to the Practice of Statistics, 6th ed., Freeman, 2009 or newer edition.
