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STA2300 Data Analysis

Semester 3, 2018 Online
Short Description: Data Analysis
Units : 1
Faculty or Section : Faculty of Health, Engineering and Sciences
School or Department : School of Agric, Comp and Environ Sciences
Student contribution band : Band 2
ASCED code : 010103 - Statistics
Grading basis : Graded
Version produced : 14 February 2019


Examiner: Christine McDonald

Other requisites

It is recommended that students have basic computing and numeracy skills.
STA2300 is not available to students who have already undertaken or intend to undertake STA3100 Evaluating Information.


Statistics are pervasive in work and life. Whether it is the planning and implementation of a survey to assess the market penetration of a new product, the design of an experiment to test the efficacy of a new drug, the gathering and summarizing of data provided by a government organization to support an argument or a summary of how well your sports team is doing, data and the discipline of statistics contributes in an essential way. Never before has some understanding of the discipline of statistics been so important to an educated person. Regardless of whether you ever need to initiate the collection or analysis of data in your future studies or future work, some understanding of statistical methods is highly desirable, if not essential, in being able to critically appraise the methods employed by others in generating information of importance to you.


Basic statistical concepts, methods and skills necessary for students in business, commerce, psychology and the physical sciences to collect, appraise, present, analyse and interpret data are developed in this course. Emphasis is placed on understanding the basic concepts and principles of dealing with data, in particular descriptive and inferential statistics. Because these concepts and methods are interdisciplinary in nature, students will encounter problems from many sources including their own area of interest. The use of statistical software is a core component of the course. The mathematical underpinnings of the methods used are not covered. Other statistics courses deal with this aspect.


On completion of this course students will be able to:

  1. Explore relationships in data and distinguish between different methods of data collection and analysis
  2. Evaluate and apply a variety of statistical inferential methods to real life situations.
  3. Use a statistical computer package to enter, summarise and analyse data.
  4. Interpret and communicate the results of statistical analyses for a diverse audience.


Description Weighting(%)
1. Exploring and understanding data: variables and values; types of data; introduction to SPSS; categorical variables; contingency tables. 8.00
2. Describing distributions: quantitative data; graphs of distributions; summary statistics. 6.00
3. Using the normal model: standardising; unstandardising; standard normal curve; using Table Z. 8.00
4. Exploring relationships between variables: scatterplots; correlation and regression; boxplots. 12.00
5. Gathering data: Observational and experimental studies; surveys; sampling methods; principles of good design; causation and confounding. 12.00
6. Randomness and probability: probability rules; events; probability models; means and standard deviation; the binomial model. 10.00
7. Sampling distribution models: proportions and means; standard error; the central limit theorem. 6.00
8. Generalising to the World at Large: introduction to hypothesis testing and confidence intervals; the sign test; sample size determination. 14.00
9. Hypothesis testing for proportions and means: z-test for proportion; one sample t-procedure for a mean; confidence intervals; level of significance; type I and type II errors. 8.00
10. Comparing means: two sample t-procedures; independent and dependent samples; confidence intervals and hypothesis testing. 8.00
11. Chi-square testing: test of independence; follow-up analysis. 8.00

Text and materials required to be purchased or accessed

ALL textbooks and materials available to be purchased can be sourced from USQ's Online Bookshop (unless otherwise stated). (

Please contact us for alternative purchase options from USQ Bookshop. (

  • De Veaux, R.D., Velleman, P.F. & Bock, D.E 2016, Stats: data and models, 4th Global edn, Pearson Education, Harlow, United Kingdom.
  • All additional study material will be provided on the course StudyDesk.
  • IBM SPSS STATISTICS BASE GRAD PACK VERSION 24.0 (SPSS Version 20.0 or later is acceptable) (Note: Oncampus students have access to this software in campus computer laboratories and are not required to purchase SPSS).

Reference materials

Reference materials are materials that, if accessed by students, may improve their knowledge and understanding of the material in the course and enrich their learning experience.

Student workload expectations

Activity Hours
Assessments 30.00
Examinations 2.00
Private Study 138.00

Assessment details

Description Marks out of Wtg (%) Due Date Notes
Assignment 1 5 5 30 Nov 2018
Assign 2 on Topics 1 to 6 20 20 20 Dec 2018
Assign 3 Up to & Inc Topic 10 25 25 29 Jan 2019
EXAMINATION 50 50 End S3 (see Examination notes below)

Description Marks out of Wtg (%) Notes
Exam (Part A) 20 20 (see exam note 1)
Exam (Part B) 30 30

Exam Notes
  1. This will be a restricted exam. The total working time for the examination (parts A and B) is 2 hours. The examination date will be available via UConnect when the official examination timetable has been released.

Important assessment information

  1. Attendance requirements:
    It is the students' responsibility to participate appropriately in all activities and to study all material provided to them or required to be accessed by them to maximise their chance of meeting the objectives of the course and to be informed of course-related activities and administration.

  2. Requirements for students to complete each assessment item satisfactorily:
    To complete an assessment item satisfactorily, students must obtain at least 50% of the marks available for that assessment item.

  3. Penalties for late submission of required work:
    Students should refer to the Assessment Procedure (point 4.2.4)

  4. Requirements for student to be awarded a passing grade in the course:
    To be assured of receiving a passing grade a student must obtain at least 50% of the total weighted marks available for the course (i.e. the Primary Hurdle), and have satisfied the Secondary Hurdle (Supervised), i.e. the end of semester examination by achieving at least 40% of the weighted marks available for that assessment item.

    Supplementary assessment may be offered where a student has undertaken all of the required summative assessment items and has passed the Primary Hurdle but failed to satisfy the Secondary Hurdle (Supervised), or has satisfied the Secondary Hurdle (Supervised) but failed to achieve a passing Final Grade by 5% or less of the total weighted Marks.

    To be awarded a passing grade for a supplementary assessment item (if applicable), a student must achieve at least 50% of the available marks for the supplementary assessment item as per the Assessment Procedure (point 4.4.2).

  5. Method used to combine assessment results to attain final grade:
    The final grades for students will be assigned on the basis of the aggregate of the weighted marks obtained for each of the summative assessment items in the course.

  6. Examination information:
    In a Restricted Examination, candidates are allowed access to specific materials during the examination. The only materials that candidates may use in the restricted examination for this course are: writing materials (non-electronic and free from material which could give the student an unfair advantage in the examination); scientific or graphics calculator(s) which cannot communicate with any other devices (students must indicate on their examination paper the make and model of any calculator(s) they use during the examination). One A4 sheet of paper, written or typed on one or both sides with any material the student wishes to include (students are required to submit this sheet of paper with the examination paper, but it will not contribute to marks for the course). Formula sheets will be provided with the examination paper. Students whose first language is not English, may take an appropriate unmarked non-electronic translation dictionary (but not technical dictionary) into the examination. Dictionaries with any handwritten notes will not be permitted. Translation dictionaries will be subject to perusal and may be removed from the candidate's possession until appropriate disciplinary action is completed if found to contain material that could give the candidate an unfair advantage.

  7. Examination period when Deferred/Supplementary examinations will be held:
    Any Deferred or Supplementary examinations for this course will be held during the next examination period.

  8. University Student Policies:
    Students should read the USQ policies: Definitions, Assessment and Student Academic Misconduct to avoid actions which might contravene University policies and practices. These policies can be found at

Other requirements

  1. Computer, e-mail and Internet access:
    Students are required to have access to a personal computer, e-mail capabilities and Internet access to UConnect. Current details of computer requirements can be found at