Outline

Overview

The aim is to introduce students to fundamental concepts in statistics and research design as applied to psychological research. These include summary descriptive statistics, an introduction to the principles and practice of research design (both quantitative and qualitative approaches), and the use of inferential statistics. Building upon this framework, the unit of study aims to develop each student's expertise in understanding the rationale for, and application of, a variety of statistical tests to the sorts of data typically obtained in psychological research.

Unit details and rules

Unit code	PSYC2012
Academic unit	Psychology Academic Operations
Credit points	6
Prohibitions ?	None
Prerequisites ?	PSYC1001 OR PSYC1002
Corequisites ?	None
Assumed knowledge ?	Recommended: HSC Mathematics, any level
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Rebecca Pinkus, rebecca.pinkus@sydney.edu.au
Lecturer(s)	Daniel Costa, daniel.costa@sydney.edu.au
	Rebecca Pinkus, rebecca.pinkus@sydney.edu.au
	Haryana Dhillon, haryana.dhillon@sydney.edu.au

Type	Description	Weight	Due	Length
Final exam (Record+)	Final online exam Open book, MCQs on lecture & tutorial content	40%	Formal exam period	2 hours
Outcomes assessed:
Placement	Research participation Be a participant in School of Psychology research and answer questions	5%	Ongoing	5 hours
Outcomes assessed:
Tutorial quiz	Quiz 1 Open book, online short answer small quiz on lecture & tutorial content	5%	Week 03 Due date: 15 Mar 2021 at 14:00	15min max
Outcomes assessed:
Tutorial quiz	Quiz 2 Open book, online short answer small quiz on lecture & tutorial content	5%	Week 04 Due date: 22 Mar 2021 at 14:00	15min max
Outcomes assessed:
Tutorial quiz	Quiz 3 Open book, online short answer small quiz on lecture & tutorial content	5%	Week 06 Due date: 12 Apr 2021 at 14:00	15min max
Outcomes assessed:
In-semester test (Record+)	In-semester exam Open book, MCQs on lecture & tutorial content	25%	Week 08 Due date: 26 Apr 2021 at 14:00	50 minutes
Outcomes assessed:
Tutorial quiz	Quiz 4 Open book, online short answer small quiz on lecture & tutorial content	5%	Week 09 Due date: 03 May 2021 at 14:00	15min max
Outcomes assessed:
Tutorial quiz	Quiz 5 Open book, online short answer small quiz on lecture & tutorial content	5%	Week 11 Due date: 17 May 2021 at 14:00	15min max
Outcomes assessed:
Tutorial quiz	Quiz 6 Open book, online short answer small quiz on lecture & tutorial content	5%	Week 13 Due date: 31 May 2021 at 14:00	15min max
Outcomes assessed:
= hurdle task ? = Type B final exam ? = Type B in-semester exam ?

Assessment summary

Research participation: Involvement in research is Psychology’s form of practical work, and you are encouraged to act as participants. You can earn up to 5% of your final grade by participating in 5 hours of research. To complete your second year research participation experience, you will answer a few simple questions about ONE of the studies you have completed via an online quiz. If you are enrolled in two units of study which allow research participation this semester, your total earned credits will be evenly distributed to each unit. Research participation is not compulsory. If you do not complete any or all of your 5 hours of research participation, you simply will not receive the marks associated with it. An alternative to research participation (a written assignment) is also available on request (before Week 6).
Quizzes: The quizzes cover recent lecture and tutorial content. They are deployed at the beginning of the Monday lectures in the weeks specified. They consist of one (multi-part) question. If you do not complete any of these quizzes, you will not receive the marks associated with it. If you have sucessfully applied for special consideration for a quiz, you will receive a marks adjustment. After two marks adjustments, the outcome for subsequent approved special considerations will be a replacement quiz on the Friday of the next week.
In-semester exam: This assessment is a cumulative assessment covering lecture and tutorial content. It is deployed at the beginning of the Monday lecture in the week specified, and it is an online MCQ exam. If you do not complete the assessment, you will not receive the marks associated with it. If you have successfully applied for special consideration, the outcome will be a replacement in-semester exam to be completed on the Friday of the following week.
Final exam: The final exam is a cumulative assessment covering lecture and tutorial content. It is an online MCQ exam. If you do not complete the assessment, you will not receive the marks associated with it. If you have successfully applied for special consideration, the outcome will be a replacement final exam to be completed during the replacement exam period.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a High distinction indicates work of an exceptional standard, a Distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100	This work shows excellent understanding of the topic and clear evidence of independent critical thought.
Distinction	75 - 84	This work shows a very good understanding of the relevant content. Some calculations or interpretations may be flawed, but a serious and sustained attempt has been made.
Credit	65 - 74	This work shows a clear understanding of the relevant material; it contains only small gaps or minor errors.
Pass	50 - 64	This work shows evidence of a satisfactory level of understanding of the relevant material; it may contain gaps, errors or other kinds of blemishes, but it is obvious that the student has read and digested material from lectures and/or tutorials.
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see sydney.edu.au/students/guide-to-grades

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Weekly schedule

WK	Topic	Learning activity
Week 01	1. The importance and ethics of statistics for psychological research; 2. What is qualitative research? When and why would I use it? 3. Variables and descriptive statistics	Lecture (3 hr)
Week 02	1. Descriptive statistics and z-scores; 2. Theory and how it influences qualitative research; 3. Linear transformations and the normal distribution	Lecture (3 hr)
Week 02	Descriptive statistics	Tutorial (2 hr)
Week 03	1. The research process and research designs; 2. Research designs and null hypothesis significance testing	Lecture (2 hr)
Week 03	Linear transformations, normal distribution, z-scores	Tutorial (2 hr)
Week 04	1. z-test - part 1; 2. z-test - part 2	Lecture (2 hr)
Week 04	NHST & z-tests	Tutorial (2 hr)
Week 05	1. t-test for a single mean - part 1; 2. Doing qualitative research: Design and data collection; 3. t-test for a single mean - part 2; confidence intervals	Lecture (3 hr)
Week 05	z-test & t-test for a single mean	Tutorial (2 hr)
Week 06	1. Related samples t-test - part 1; 2. Related samples t-test - part 2; power and effect size	Lecture (2 hr)
Week 06	Confidence intervals	Tutorial (2 hr)
Week 07	1. Independent samples t-test - part 1; 2. Doing qualitative research: Data analysis and reporting; 3. Independent samples t-test - part 2	Lecture (3 hr)
Week 07	Related samples t-test	Tutorial (2 hr)
Week 08	1. One-way ANOVA - part 1; 2. One-way ANOVA - part 2	Lecture (2 hr)
Week 08	Independent samples t-test	Tutorial (2 hr)
Week 09	1. One-way ANOVA - part 3; Two-way ANOVA - part 1; 2. Two-way ANOVA - part 2	Lecture (2 hr)
Week 09	One-way ANOVA	Tutorial (2 hr)
Week 10	1. Correlation - part 1; 2. Doing qualitative research: Interpretation and reporting; 3. Correlation - part 2	Lecture (3 hr)
Week 10	Two-way ANOVA	Tutorial (2 hr)
Week 11	1. Regression - part 1; 2. Regression - part 2	Lecture (2 hr)
Week 11	Correlation	Tutorial (2 hr)
Week 12	1. Chi-square tests - part 1; 2. Putting the 'quality' in qualitative research; 3. Chi-square tests - part 2	Lecture (3 hr)
Week 12	Regression	Tutorial (2 hr)
Week 13	1. Reliability, validity and replicability; 2. Test selection and revision	Lecture (2 hr)
Week 13	Chi-square and revision	Tutorial (2 hr)

Attendance and class requirements

Due to the exceptional circumstances caused by the COVID-19 pandemic, attendance requirements for this unit of study have been amended. Where online tutorials/workshops/virtual laboratories have been scheduled, students should make every effort to attend and participate at the scheduled time. Penalties will not be applied if technical issues, etc. prevent attendance at a specific online class. In that case, students should discuss the problem with the coordinator, and attend another session, if available.

Students will need to bring a calculator to all tutorials and assessments. The calculator should have statistical functions. The calculators used in HSC mathematics courses will be suitable.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

All of the readings in this unit of study are recommended; none are required.

The main recommended readings come from two interactive textbooks from Top Hat publishers:

• Hayward, S. et al. (2018). Statistics for social sciences: A Top Hat interactive text.
• Freberg, L. et al. (2018). Research methods in psychological science: A Top Hat interactive text.

By special arrangement with the publishers, the entire Statistics and five chapters from the Research methods interactive texts are being packaged together for PSYC2012. For more information, please refer to the details on Canvas.

Two additional recommended resources are the two versions of David Howell’s texts:

Howell, D. C. (2012). Statistical methods for psychology (8th ed.). Belmont, CA: Wadsworth Cengage Learning.
Howell, D. C. (2017). Fundamental statistics for the behavioral sciences (9th ed.). Belmont, CA: Wadsworth Cengage Learning.
- For those students who have done no statistics before (PSYC1001/1002 not included) and are apprehensive, the Fundamental textbook is recommended. For those who have some statistical training, the Statistical methods textbook is more advanced and a valuable reference for further study in Psychology. Earlier editions of the textbooks are suitable. See Canvas for updated pricing and library availability information.

For Statistics, useful resources are:

Aron, A., Aron, E. N., & Coups, E. (2013). Statistics for psychology (6th ed.). Upper Saddle River, NJ: Prentice Hall.
*Field, A. (2013). Discovering statistics using IBM SPSS statistics (4th ed.). New York: Sage.
King, B. M., & Minium, E. W. (2003). Statistical reasoning in psychology and education (4th ed.). New York: Wiley.
Wheelan, C. (2013). Naked statistics: Stripping the dread from the data. New York: Norton.

*This text is useful for understanding statistics as well as SPSS.

For Research Methods, useful resources are:

Gravetter, F. J., & Forzano, L. B. (2016). Research methods for the behavioral sciences (5th ed.). Stamford, CT: Cengage Learning.
Mitchell, M, L., & Jolley, J. M. (2012). Research design explained (8th ed.). Belmont, CA: Thomson Wadsworth.
*Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3, 77-101.
*Chiovitti, R. F., & Piran, N. (2003). Rigour and grounded theory research. Journal of Advanced Nursing, 44, 427-435.
*Gale, N. K., Heath, G., Cameron, E., Rashid, S., & Redwood, S. (2013). Using the framework method for the analysis of qualitative data in multi-disciplinary heath research. BMC Medical Research Methodology, 13, 117. https://doi.org/10.1186/1471-2288-13-117 (Links to an external site.)
*Holloway, I., & Todres, L. (2003). The status of method: Flexibility, consistency and coherence. Qualitative Research, 3, 345-357.

*These resources are useful for qualitative research methods.

For using SPSS, some useful resources are:

Allen, P., Bennett, K., & Heritage, B. (2014). SPSS statistics version 22: A practical guide (3rd ed.). Melbourne, VIC, Australia: Cengage.
Pallant, J. F. (2013). SPSS survival manual: A step by step guide to data analysis using IBM SPSS (5th ed.). Crows Nest, NSW, Australia: Allen & Unwin.

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. Calculate and interpret descriptive statistics such as measures of central tendency and variability
LO2. Demonstrate understanding of graphical and tabular representations of data, and be able to use statistical tables
LO3. Conduct significance tests for statistical hypotheses relevant to Psychology
LO4. Compute and interpret confidence intervals and other effect size indices
LO5. Describe, apply, and evaluate the different quantitative research methods used by psychologists
LO6. Describe and define qualitative research methods used by psychologists
LO7. Demonstrate practical skills in laboratory-based and other psychological research
LO8. Recognise potential bias in human thinking, including cultural biases in interpretation of research
LO9. Use information in an ethical manner (e.g., acknowledge and respect work and intellectual property rights of others through appropriate citations in oral and written communication); understand the ethical obligations of research scientists and understand best practice in research design

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

In response to previous student feedback, the tutorial tests have been replaced with smaller assessments (quizzes). The duration of these assessments has been designed to better accommodate the constraints of an online format. The qualitative content has been interwoven throughout the semester. Students are invited to provide feedback about these changes.

Additional information

SIGNING UP FOR STUDIES ON SONA

The website to sign up for experiments is linked to from Canvas, but is an external website.

Your login and password is the unikey and unipass you use for Canvas and if you navigate to SONA directly from Canvas you won't have to log in again. However if you are a late enrolment this will not work until you are added to SONA. All students we know of are enrolled in the system from Week 1, and we update this list with new enrolments every week until all enrolments are accounted for. If you are a late enrolment, then simply wait and within a week you will be added.

Within the first few weeks, you will be offered the opportunity to complete a ‘pre-screen’ questionnaire. You do not have to complete this. If you choose to, then allow 30min to complete it – and you will receive 30min credit time (0.5%). The aim of the pre-screen is to allow researchers to more efficiently select subjects for later studies, but if you choose not to complete it you will still be able to participate in most studies.

You may browse for available studies, and sign-up for those you are interested in. Realise that each sign-up is an appointment you have with a researcher. The penalty for breaking an appointment if you do not cancel more than 24 hours before the study runs, is half a credit point. If you accumulate more than 5 penalties your access to SONA will be suspended.

Importantly, the online sign-up itself constitutes your informed consent to participate, so read the description well. Understand this:

By signing up to an experiment on SONA, I am giving my consent and I acknowledge that:

I have read the procedures required for the project and understand the time involved, and any questions I have about the project have been answered to my satisfaction.
I have read the project information and have been given the opportunity to discuss the information and my involvement in the project with the researcher/s.
I understand that I can withdraw from the study at any time once I begin, without affecting my relationship with the researchers now or in the future.
I understand that my involvement is strictly confidential and no information about me will be used in any way that reveals my identity.

WHERE TO ASK FOR HELP*

*Do not ask the PSYC2012 instructors for assistance with SONA. See details on troubleshooting below.

I don’t understand how to use SONA	Read this section. Check the online documentation on SONA. Ask your colleagues.
I am unsure of what my password is	Click on “Lost your password?” on the SONA website and enter your UNIKEY. You MUST have access to your university email address.
SONA does not recognize my UNIKEY	Check you’ve entered your UNIKEY correctly. If you have enrolled late, then simply wait (SONA is updated weekly with new enrolments). If the problem persists for more than a week, email the Subject Pool Administrator (psychology.research@sydney.edu.au) with the details.
I’ve forgotten the study details	Login to SONA, and find your appointment slot – the details will always be there
I cannot make the study (>24 hours before)	CANCEL THE APPOINTMENT YOURSELF. Simply login and scroll down to your appointments to do this. There is no need to email anyone.
I cannot make the experiment (<24 hours before)	Login to SONA, then find the researcher’s contact details – contact them and say you cannot make the time. Unless you apply for special consideration you will not necessarily escape a penalty, but you have saved them the trouble of waiting for you. NB: There’s no point ‘replying’ to any automated reminder you will be sent, since you would be talking to a computer.
Where is the room?	The location is listed on the SONA website. Depending on how late you have left it to find out, you may want to contact the researcher by email or phone, or consult a map on the University of Sydney website.
I disagree with a penalty	Contact the researcher first – login to SONA, find their details and email or phone them.
I have read all of this documentation and I don't understand the SONA rules (e.g., cancellation issues; excused vs. unexcused absences).	Contact Dr Caleb Owens: caleb.owens@sydney.edu.au. Make sure to include the details of the experiment name, time and date of sign-up/cancellation, etc.
I have a technical issue with SONA (e.g., password is not working; inability to access the SONA login page).	Contact the Subject Pool Administrator psychology.research@sydney.edu.au. Make sure to include details about the technical issues.
I have a problem with the researcher	Contact the Subject Pool Administrator psychology.research@sydney.edu.au. Be sure to cite the experiment name and the names of the researchers involved.
I have a problem with the research	Contact the Deputy Manager, Human Ethics Administration, University of Sydney +61 2 8627 8176 (Telephone); +61 2 8627 8177 (Facsimile) or ro.humanethics@sydney.edu.au. Include as much information as possible.

Work, health and safety

We are governed by the Work Health and Safety Act 2011, Work Health and Safety Regulation 2011 and Codes of Practice. Penalties for non-compliance have increased. Everyone has a responsibility for health and safety at work. The University’s Work Health and Safety policy explains the responsibilities and expectations of workers and others, and the procedures for managing WHS risks associated with University activities.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect

Current students

PSYC2012: Statistics and Research Methods for Psych

Semester 1, 2021 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect