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Unit outline_

PSYC2012: Statistics and Research Methods for Psych

Semester 1, 2022 [Normal day] - Remote

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

Academic unit Psychology Academic Operations
Credit points 6
Prerequisites
? 
PSYC1001 OR PSYC1002
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

Recommended: HSC Mathematics, any level

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Daniel Costa, daniel.costa@sydney.edu.au
Type Description Weight Due Length
Final exam (Record+) Type B final exam hurdle task Final online exam
Open book, MCQs on lecture & tutorial content
40% Formal exam period 2 hours
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO8 LO9
Placement Research participation
Be a participant in School of Psychology research and answer questions
5% Ongoing 5 hours
Outcomes assessed: LO7 LO8 LO9
Tutorial quiz Quiz 1
Open book, online short answer small quiz on lecture & tutorial content
5% Week 03
Due date: 07 Mar 2022 at 14:00
15min max
Outcomes assessed: LO1 LO7 LO5 LO2
Tutorial quiz Quiz 2
Open book, online short answer small quiz on lecture & tutorial content
5% Week 04
Due date: 14 Mar 2022 at 14:00
15min max
Outcomes assessed: LO1 LO7 LO5 LO4 LO3 LO2
Tutorial quiz Quiz 3
Open book, online short answer small quiz on lecture & tutorial content
5% Week 06
Due date: 28 Mar 2022 at 14:00
15min max
Outcomes assessed: LO1 LO7 LO5 LO4 LO3 LO2
In-semester test (Record+) Type B in-semester exam In-semester exam
Open book, MCQs on lecture & tutorial content
25% Week 08
Due date: 11 Apr 2022 at 14:00
50 minutes
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO8 LO9
Tutorial quiz Quiz 4
Open book, online short answer small quiz on lecture & tutorial content
5% Week 09
Due date: 26 Apr 2022 at 14:00
15min max
Outcomes assessed: LO1 LO7 LO5 LO4 LO3 LO2
Tutorial quiz Quiz 5
Open book, online short answer small quiz on lecture & tutorial content
5% Week 11
Due date: 09 May 2022 at 14:00
15min max
Outcomes assessed: LO1 LO7 LO5 LO4 LO3 LO2
Tutorial quiz Quiz 6
Open book, online short answer small quiz on lecture & tutorial content
5% Week 13
Due date: 23 May 2022 at 14:00
15min max
Outcomes assessed: LO1 LO7 LO5 LO4 LO3 LO2
hurdle task = hurdle task ?
Type B final exam = Type B final exam ?
Type B in-semester 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. The final quiz mark will be the average of your best four quiz marks. If you do not complete any of these quizzes, you will not receive the marks associated with it. If you complete fewer than four quizzes and have successfully applied for special consideration for a quiz, you will receive a marks adjustment.
  • 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 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.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

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.

WK Topic Learning activity Learning outcomes
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) LO1 LO2 LO6 LO8 LO9
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) LO1 LO2 LO6 LO9
Descriptive statistics Tutorial (2 hr) LO1 LO2 LO7
Week 03 1. The research process and research designs; 2. Research designs and null hypothesis significance testing Lecture (2 hr) LO3 LO5 LO8 LO9
Linear transformations, normal distribution, z-scores Tutorial (2 hr) LO1 LO2 LO7
Week 04 1. z-test - part 1; 2. z-test - part 2 Lecture (2 hr) LO2 LO3
NHST & z-tests Tutorial (2 hr) LO2 LO3 LO7
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) LO3 LO4 LO6 LO8
z-test & t-test for a single mean Tutorial (2 hr) LO2 LO3 LO7
Week 06 1. Related samples t-test - part 1; 2. Related samples t-test - part 2; power and effect size Lecture (2 hr) LO3 LO4 LO5
Confidence intervals Tutorial (2 hr) LO2 LO3 LO4 LO7 LO9
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) LO3 LO5 LO6
Related samples t-test Tutorial (2 hr) LO2 LO3 LO7
Week 08 1. One-way ANOVA - part 1; 2. One-way ANOVA - part 2 Lecture (2 hr) LO2 LO3 LO5
Independent samples t-test Tutorial (2 hr) LO2 LO3 LO7
Week 09 1. One-way ANOVA - part 3; Two-way ANOVA - part 1; 2. Two-way ANOVA - part 2 Lecture (2 hr) LO2 LO3 LO5
One-way ANOVA Tutorial (2 hr) LO2 LO3 LO7
Week 10 1. Correlation - part 1; 2. Doing qualitative research: Interpretation and reporting; 3. Correlation - part 2 Lecture (3 hr) LO2 LO3 LO5 LO6 LO8
Two-way ANOVA Tutorial (2 hr) LO2 LO3 LO7
Week 11 1. Regression - part 1; 2. Regression - part 2 Lecture (2 hr) LO2 LO3 LO4 LO5
Correlation Tutorial (2 hr) LO2 LO3 LO7
Week 12 1. Chi-square tests - part 1; 2. Putting the 'quality' in qualitative research; 3. Chi-square tests - part 2 Lecture (3 hr) LO2 LO3 LO5 LO6
Regression Tutorial (2 hr) LO2 LO3 LO7
Week 13 1. Reliability, validity and replicability; 2. Test selection and revision Lecture (2 hr) LO2 LO3 LO4 LO5 LO8 LO9
Chi-square and revision Tutorial (2 hr) LO2 LO3 LO7

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 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.

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
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

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.

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:

  1. 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.
  2. 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.
  3. 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.
  4. 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.