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STA3100 Evaluating Information

Semester 2, 2012 On-campus Toowoomba
Units : 1
Faculty or Section : Faculty of Sciences
School or Department : Maths and Computing
Version produced : 30 December 2013

Contents on this page


Examiner: Christine McDonald
Moderator: Shahjahan Khan

Other requisites

STA3100 cannot be taken in conjunction with STA2300 Data Analysis.


An understanding of our society relies on the collection, analysis, interpretation, and dissemination of information about the people within our society. This course introduces basic concepts relevant to the effective collection, analysis, and interpretation of quantitative information from individuals and groups of individuals. An understanding of these concepts is essential to students in behavioural sciences, health sciences, educational studies, sociology, humanities, political science, business and management studies, legal studies, journalism and any discipline involving the initiation or critical appraisal of studies of social phenomena. Active participants should obtain enough knowledge to understand and critically analyse reports of many social science studies and develop sufficient practical skills to interpret information produced by a statistical software package. This course provides the foundations for application and further development in a range of programs in the Business, Education, Sciences and Arts Faculties.


Students are introduced to basic concepts and tools commonly involved in collecting, managing, summarizing, analysing, interpreting, and presenting quantitative data. The course has been designed for students in the social sciences by its choice of topics, examples, and exercises. No prior statistical or mathematical knowledge is assumed. Methods of descriptive and inferential statistics are introduced. Issues related to causation and confounding; the nature of variability, the reliability of summary statistics, the limitations and assumptions underpinning statistical techniques; the appropriate use of language in interpreting an analysis; and the use of computer output in understanding data summary and analysis are explored. The emphasis is on the concepts, interpretations, and applications of statistics as used in the analysis of social science data, rather than on mathematical or computational aspects. The use of case studies is emphasised and writing of reports facilitated.


On completion of this course, students will be able to:

  1. use appropriate graphical and numerical tools for organising, describing and displaying data
  2. apply appropriate sampling methods to the collection of observational and experimental data
  3. make judgments from surveys and experiments
  4. explain relationships between variables
  5. explain trends in data
  6. make appropriate decisions in the face of uncertainty
  7. critically evaluate information presented in academic literature and the media


Description Weighting(%)
1. Introduction to social science research data:
benefits and risks of using statistics, making sense of media reports, defining what is being measured.
2. Sampling, observational studies, surveys and experiments:
Research strategies, sampling methods, difficulties and disasters in sampling. Designing observational studies, difficulties and disasters in observational studies. Designing experiments, difficulties and disasters in experimental studies. Principles of control, random assignment, replication; single and double blinding.
3. Measurement and data description:
Variables, values and labels; data entry, checking and formatting; codebooks. Levels of measurement; nominal, ordinal, interval; continuous and discrete.
4. Data display and description:
Data distributions: bar graphs, stemplots, histograms, boxplots. Measures of central tendency; means, medians, percentiles, ranks. Measure of spread: standard deviations, range, IQR. z-scores; relevance, applications. Skewness and outliers. The normal distribution; proportions and scores.
5. Relationships between measurement variables: statistical relationships, scatterplots, correlation, causation, lurking variables, internal and external validity. 20.00
6. Relationships between categorical variables: Contingency tables, frequencies, percentages, proportions, probabilities. Conditioning: explanatory (independent) and response (dependent) variables, independence of variables, assessing statistical significance, chi-square test of independence. 10.00
7. Association and significance:
Measures of association; expected and observed frequencies; the chi-square test of independence. Logic of hypothesis testing; null and alternative hypotheses; Type I and II errors, power; P-values and their interpretation.
8. Making judgments from surveys and experiments:
Populations and samples. Interpretation of confidence intervals. Hypothesis testing about proportions and means. Impact of sample size; statistical and practical significance.

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. (

  • Utts, J M 2005, Seeing Through Statistics, 3rd edn, Thompson.

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.
  • Argyrous, G 2000, Statistics for social and health research with a guide to SPSS, Sage, London.
  • Bowers, D 1996, Statistics from scratch: an introduction for health care professionals, Wiley, Chichester, New York.
  • Coakes, SJ, Steed, LG & Ong, C 2009, SPSS: Analysis without anguish, Version 16.0 for Windows, Wiley, Milton, Queensland.
  • Fink, A 2009, How to conduct surveys: a step by step guide, 4th edn, Sage, Thousand Oaks, California.
  • Fowler, J, Chevannes, M, & Jarvis, P 2002, Practical statistics for nursing and health care: a modern introduction, Wiley, New York.
  • Hinton, PR 2004, Statistics explained, 2nd edn, Routledge, London.
  • Jaeger, RM 1990, Statistics: A spectator sport, Sage, Newbury Park, California.
  • Jaisingh, LR 2006, Statistics for the utterly confused, 2nd edn, McGraw-Hill, New York.
  • Kranzler, JH 2003, Statistics for the terrified, 3rd edn, Prentice-Hall, Upper Saddle River, New Jersey.
  • Kurtz, NR 1999, Statistical Analysis for the Social Sciences, Allyn & Bacon, Boston, Massachussets.
  • Madrigal, L 1998, Statistics for anthropology, CUP, Cambridge.
  • Parry, LJ and Traill, A 1999, Statistics explained, Addison-Wesley, Reading, Massachussets.
  • Salkind, NJ 2004, Statistics for People who (think they) hate statistics, 2nd edn, Sage, Thousand Oaks, California.
  • Weinberg, SL, Abramowitz, SK 2002, Data analysis for the behavioural sciences using SPSS, CUP, Cambridge, UK.
  • Williams, F 1992, Reasoning with statistics: how to read quantitative research, 4th edn, Harcourt Brace Jovanovich, Fort Worth, Texas.

Student workload requirements

Activity Hours
Assessments 20.00
Examinations 2.00
Lectures 26.00
Private Study 94.00
Tutorials 26.00

Assessment details

Description Marks out of Wtg (%) Due Date Notes
ASSIGNMENT 1 10 4 03 Aug 2012
CMA 1 20 8 13 Aug 2012
ASSIGNMENT 2 100 15 03 Sep 2012
CMA 2 20 8 17 Sep 2012
INDIVIDUAL REPORT 100 25 08 Oct 2012

Important assessment information

  1. Attendance requirements:
    It is the students' responsibility to attend and participate appropriately in all activities (such as lectures, tutorials, laboratories and practical work) scheduled for them, 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 satisfactorily complete an assessment item a student must achieve at least 50% of the marks or a grade of at least C-. Students do not have to satisfactorily complete each assessment item to be awarded a passing grade in this course. Refer to Statement 4 below for the requirements to receive a passing grade in this course.

  3. Penalties for late submission of required work:
    If students submit assignments after the due date without (prior) approval of the examiner then a penalty of 5% of the total marks gained by the student for the assignment may apply for each working day late up to ten working days at which time a mark of zero may be recorded. No assignments will be accepted after model answers have been posted.

  4. Requirements for student to be awarded a passing grade in the course:
    To be assured of receiving a passing grade a student must achieve at least 50% of the total weighted marks available for the course.

  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:
    Candidates are allowed access only to specific materials during a Restricted 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); calculators which cannot hold textual information (students must indicate on their examination paper the make and model of any calculator(s) they use during the examination). 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

Assessment notes

  1. The due date for an assignment is the date by which a student must despatch the assignment to the USQ. The onus is on the student to provide proof of the despatch date, if requested by the Examiner. Students must retain a copy of each item submitted for assessment. This should be despatched to USQ within 24 hours of receipt of a request to do so. The examiner may grant an extension of the due date of an assignment in extenuating circumstances. The examiner may grant an extension of the due date of an assignment in extenuating circumstances.