|Semester 2, 2021 Online|
|Short Description:||Evaluating Information|
|Faculty or Section :||Faculty of Health, Engineering and Sciences|
|School or Department :||School of Sciences|
|Student contribution band :||Band 1|
|ASCED code :||010103 - Statistics|
|Grading basis :||Graded|
|Version produced :||19 June 2021|
Examiner: Catriona Croton
Enrolment is not permitted in STA2100 if STA3100 has been previously completed.
STA2100 is not available to students who have already completed STA2300 Data Analysis or equivalent.
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.
Students are introduced to basic concepts and tools commonly involved in collecting, managing, summarizing, analysing, interpreting, and presenting quantitative data. 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 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:
- Explain relationships and trends in data and distinguish between different methods of data collection.
- Critically evaluate information presented in academic literature and the media.
- Communicate the interpretation of statistical information.
- Independently develop and conduct a statistical study and appropriately report results.
Introduction to research data:
benefits and risks of using statistics, making sense of media reports, defining what is being measured.
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.
Measurement and data description:
Variables, values and labels; data entry, checking and formatting; codebooks. Levels of measurement; nominal, ordinal, interval; continuous and discrete.
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|
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.
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). (https://omnia.usq.edu.au/textbooks/?year=2021&sem=02&subject1=STA2100)
Please contact us for alternative purchase options from USQ Bookshop. (https://omnia.usq.edu.au/info/contact/)
Student workload expectations
|Description||Marks out of||Wtg (%)||Due Date||Notes|
|Assignment 1||10||10||27 Jul 2021|
|Project Proposal||100||20||24 Aug 2021|
|Project||100||30||07 Oct 2021|
|Open Examination - Online||80||40||End S2||(see note 1)|
- This will be an online exam. Students will be provided further instruction regarding the exam by their course examiner via StudyDesk. The examination date will be available via UConnect when the Alternate Assessment Schedule has been released.
Important assessment information
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.
Requirements for students to complete each assessment item satisfactorily:
To complete each of the assessment items satisfactorily, students must obtain at least 50% of the marks available for each assessment item.
Penalties for late submission of required work:
Students should refer to the Assessment Procedure http://policy.usq.edu.au/documents.php?id=14749PL (point 4.2.4)
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.
Supplementary assessment may be offered where a student has 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 http://policy.usq.edu.au/documents/14749PL (point 4.4.2).
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.
An Open Examination is one in which candidates may have access to any printed or written material and a calculator during the examination.
Examination period when Deferred/Supplementary examinations will be held:
The details regarding deferred/supplementary examinations will be communicated at a later date.
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 http://policy.usq.edu.au.
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 http://www.usq.edu.au/current-students/support/computing/hardware
Students can expect that questions in assessment items in this course may draw upon knowledge and skills that they can reasonably be expected to have acquired before enrolling in this course. This includes knowledge contained in pre-requisite courses and appropriate communication, information literacy, analytical, critical thinking, problem solving or numeracy skills. Students who do not possess such knowledge and skills should not expect the same grades as those students who do possess them.