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STA2300 Data Analysis

Semester 2, 2019 On-campus Springfield
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 : 22 February 2019


Examiner: Shahjahan Khan


Enrolment is not permitted in STA2300 if STA8170 or STA3100 has been previously completed.

Other requisites

It is recommended that students have basic computing and numeracy skills.


This course aims to provide students who have limited knowledge of statistics, with the fundamental statistical concepts, methods and skills necessary in order to undertake or critically appraise quantitative methods and the interpretation of subsequent results. The course is aimed at developing statistical literacy in students from a variety of disciplines, including science, psychology, the physical sciences, business, commerce, and IT and is a pre-requisite for most high-level statistics courses.


This course focuses primarily on the appropriate application, interpretation and communication of foundational descriptive and inferential statistical methods. Emphasis is placed on understanding the concepts and principles associated with dealing with data, in particular descriptive and inferential statistics. Data sets from a range of disciplines are included as well as examples of statistics presented in popular media. Core components of the course include the use of statistical software and the development of problem solving and quantitative skills relevant to many disciplines of study. Note: The mathematical underpinnings of the methods used are not covered; other statistics courses cover this aspect.


On completion of this course students should 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 25.0 (SPSS Version 20.0 or later is acceptable) (Note: This software can be accessed when on campus in computer laboratories and the library. Otherwise, a one year student license can be purchased on disk from the USQ Bookshop, or a six-month license for a download version can be purchased online from the Australia and New Zealand distributors of SPSS, Hearne Software. Before deciding to choose the download option check that the size of the download in compatible with your internet quota and speed. Be aware that the SPSS student license only allows limited reinstalment within the designated license period from initial installation).

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
Lectures 26.00
Private Study 81.00
Tutorials 26.00

Assessment details

Description Marks out of Wtg (%) Due Date Notes
Assignment 1 5 5 25 Jul 2019
Assign 2 on Topics 1 to 6 20 20 03 Sep 2019
Assign 3 Up to & Inc Topic 10 25 25 15 Oct 2019
EXAMINATION 50 50 End S2 (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 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 Section 4.4.2 of the Assessment Procedure.

  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