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JOHN CABOT UNIVERSITY
COURSE CODE: "PS 208-2"
COURSE NAME: "Introduction to Statistical Analyses of Psychological Data"
SEMESTER & YEAR:
Fall 2022
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SYLLABUS
INSTRUCTOR:
Merel Keijsers
EMAIL: [email protected]
HOURS:
MW 11:30 AM 12:45 PM
TOTAL NO. OF CONTACT HOURS:
45
CREDITS:
3
PREREQUISITES:
Prerequisite: PS 210
OFFICE HOURS:
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COURSE DESCRIPTION:
The course introduces students to the statistical methods commonly used in psychological research and provides the
necessary foundation in statistical reasoning to think critically about psychological findings reported in research articles and
in the media. Students will learn how to use statistics in the context of research, what statistical test is appropriate given the
research design and the type of data collected, and why statistical tests are used to draw conclusion in research. They will also
learn how to write up their own statistical analyses in APA style. The course includes a laboratory component where students
will familiarize themselves with statistical software and will learn how to use it for managing and analyzing data. Sample
topics include: scales of measurements, measures of central tendency and variability, the logic of hypothesis testing
(including limitations and modern approaches), parametric and nonparametric tests, effect size, confidence intervals, power
and sample size.
Minimum passing grade for students enrolled for the BA in Psychological science: C-
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SUMMARY OF COURSE CONTENT:
The course introduces students to the statistical models and tests commonly used in psychological research and provides the necessary foundation in statistical reasoning to think critically about psychological findings reported in research articles and in the media. Students will learn how to use statistics in the context of research, what statistical test is appropriate given the research design and the type of data collected, and why statistical tests are used to draw conclusion in research. They will also learn how to carry out statistical tests in Jamovi, and to write up their own statistical analyses in APA style.
The tests covered in the course are discussed from three perspectives: the theoretical (a lecture on the theoretical and mathematical underpinnings of the test), the applied (an interactive discussion session in which an academic paper using said test is being used) and the practical (a laboratory session where students will use statistical software to carry out the test in question). Similarly, the overall course grade will be composed of a theoretical (midterm/final), practical (three assignments), and applied (presentation and final) assessment.
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LEARNING OUTCOMES:
By the end of this course, students should be able to
- Identify and use appropriate statistical procedures and terminology.
- Be comfortable using statistical software to manage and analyze data.
- Understand how statistical methods are used to test hypotheses.
- Interpret quantitative data displayed in statistics, graphs, and tables, including statistical symbols in research reports.
- Interpret the outcomes of the (discussed) statistical tests both in terms of generated output and statistics reported in academic papers.
- Accurately summarize and present statistical results in a meaningful manner both orally and in writing. Write using APA Style.
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TEXTBOOK:
| Book Title | Author | Publisher | ISBN number | Library Call Number | Comments | Format | Local Bookstore | Online Purchase |
| Discovering statistics using R | Andy Field, Jeremy Miles, Zoe Field | SAGE publications | ISBN-13: 978-1446200469 | | Students may choose if they want to find a hard copy or an online PDF version of the book. In spite of the title, we will not use R as statistical software for this course. The book however also provides a solid theoretical introduction to statistics, which is why we'll be using it. | | | |
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REQUIRED RESERVED READING:
RECOMMENDED RESERVED READING:
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GRADING POLICY
-ASSESSMENT METHODS:
| Assignment | Guidelines | Weight |
| Assignment 1 | Students will be required to carry out & report on the t-test. | 18% |
| Assignment 2 | Students will be required to carry out & report on the ANOVA. | 18% |
| Assignment 3 | Students will be required to carry out & report on a logistic regression. | 18% |
| Group presentation | Students will have to form groups of 3-4 students and give a 20 minute presentation of a topic of their choice. A list of suggested topics will be made available on Moodle. This is a group grade. | 10% |
| Midterm | The midterm will be in-person and assess students' understanding of the principles of statistics | 18% |
| Final | The final will be a take-home exam and assess both students' understanding of the theoretical underpinnings of statistics, and their applied skills (e.g. interpreting statistical results). | 18% |
-ASSESSMENT CRITERIA:
AWork of this quality directly addresses the question or problem raised and provides a coherent argument displaying an extensive knowledge of relevant information or content. This type of work demonstrates the ability to critically evaluate concepts and theory and has an element of novelty and originality. There is clear evidence of a significant amount of reading beyond that required for the course.
BThis is highly competent level of performance and directly addresses the question or problem raised.There is a demonstration of some ability to critically evaluatetheory and concepts and relate them to practice. Discussions reflect the student’s own arguments and are not simply a repetition of standard lecture andreference material. The work does not suffer from any major errors or omissions and provides evidence of reading beyond the required assignments.
CThis is an acceptable level of performance and provides answers that are clear but limited, reflecting the information offered in the lectures and reference readings.
DThis level of performances demonstrates that the student lacks a coherent grasp of the material.Important information is omitted and irrelevant points included.In effect, the student has barely done enough to persuade the instructor that s/he should not fail.
FThis work fails to show any knowledge or understanding of the issues raised in the question. Most of the material in the answer is irrelevant.
-ATTENDANCE REQUIREMENTS:
ATTENDANCE REQUIREMENTS AND EXAMINATION POLICY
You cannot make-up a major exam (midterm or final) without the permission of the Dean’s Office. The Dean’s Office will grant such permission only when the absence was caused by a serious impediment, such as a documented illness, hospitalization or death in the immediate family (in which you must attend the funeral) or other situations of similar gravity. Absences due to other meaningful conflicts, such as job interviews, family celebrations, travel difficulties, student misunderstandings or personal convenience, will not be excused. Students who will be absent from a major exam must notify the Dean’s Office prior to that exam. Absences from class due to the observance of a religious holiday will normally be excused. Individual students who will have to miss class to observe a religious holiday should notify the instructor by the end of the Add/Drop period to make prior arrangements for making up any work that will be missed. The final exam period runs until 8 December 2022.
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ACADEMIC HONESTY
As stated in the university catalog, any student who commits an act of academic
dishonesty will receive a failing grade on the work in which the dishonesty occurred.
In addition, acts of academic dishonesty, irrespective of the weight of the assignment,
may result in the student receiving a failing grade in the course. Instances of
academic dishonesty will be reported to the Dean of Academic Affairs. A student
who is reported twice for academic dishonesty is subject to summary dismissal from
the University. In such a case, the Academic Council will then make a recommendation
to the President, who will make the final decision.
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STUDENTS WITH LEARNING OR OTHER DISABILITIES
John Cabot University does not discriminate on the basis of disability or handicap.
Students with approved accommodations must inform their professors at the beginning
of the term. Please see the website for the complete policy.
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SCHEDULE
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| Week |
Topic |
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5-11 Sep
12-18 Sep
19-25 Sep
26 Sep- 2 Oct
3-9 Oct
10-16 Oct
17-23 Oct
24-30 Oct
31 Oct- 6 Nov
7-13 Nov
14-20 Nov
21-27 Nov
28 Nov - 4 Dec
5-11 Dec
12-18 Dec
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Intro & Descriptive statistics (I)
Descriptive statistics (II) & Hypothesis testing (I)
Hypothesis testing (II) & t-test (theory)
t-test (applied) & t-test (lab)
Linear models (theory) & one-way ANOVA (theory)
One-way ANOVA (applied) & one-way ANOVA (lab)
Factorial ANOVA (theory) & factorial ANOVA (applied)
Factorial ANOVA (lab) & regression (theory)
regression (applied) & regression (lab)
Review session & Midterm
Categorical data (theory) & categorical data (applied)
Categorical data (lab) & Correlation/reliability
Correlation/reliability (applied) & correlation/reliability (lab)
Group presentations & Review session
Finals week (take home exam)
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