Buscar

... RESEARCH METHODS IN PSYCHOLOGY PSYCHOLOGY 211-01 SPRING 2022 Monday & Wednesday: 12:00pM-1:50pM, Lynch Memorial Hall, Room 190 COURSE INSTRUCTOR (WHO IS TEACHING THIS COURSE?) Rachel Albert, Ph.D. (she/her) Phone: 717-867-6192 E-mail: ralbert@lvc.edu Office: 287F Lynch Student drop-in meeting times (aka Office hours) are Mondays 2-3 and Fridays 12-1 (Lynch 287F/zoom), Tuesdays 2-3 in zoom or by appt. COURSE DESCRIPTION (WHAT IS THIS COURSE ABOUT?) This course is an introduction to the technical aspects of scientific psychology. Accomplishing this requires the development of a particular way of thinking and communicating. To address these goals, the course is structured in a way that requires students to engage regularly with the material in different ways. You will complete homework assignments that will ask you to apply the material; youll read and analyze research articles; and youll conduct two research projects that will be communicated in an APA-style posters and a presentation, respectively. COURSE READINGS (WHAT WILL BE READ IN THIS COURSE?) Jhangiani, R. S., Chiang, I. A., Cuttler, C., & Leighton, D. C. (2019). Research methods in psychology (4th Edition). Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. Available for download for free at https://kpu.pressbooks.pub/psychmethods4e/ or a hard-copy at Amazon.com (ISBN: 9781085976923; REQUIRED) Research Articles: There is a list of required research articles available on Canvas in the Appendix A. Students must locate and download these articles using the appropriate library database. (REQUIRED) Silvia, P. J. (2015). Write it up: Practical strategies for writing an publishing journal articles. American Psychological Association (ISBN: 9781433818141; SUGGESTED/NOT REQUIRED) Kitchens, M. B. (2020). Writing an APA-Style research paper: A guide to writing research papers in psychology. Department of Psychology, Lebanon Valley College. (available on Canvas; SUGGESTED/NOT REQUIRED) COURSE LEARNING OUTCOMES (WHAT WILL I LEARN IN THIS COURSE?) The Department of Psychology learning goals are designed to help students be life-long learners. This course primarily focuses on those marked with and secondarily on those marked with O: Analyze Assemble Acquire Department Goals & Objectives O Students will demonstrate effective reading comprehension skills. O Students will demonstrate effective information literacy skills. Students will articulate the relationship between theory and data. Students will synthesize information from different sources when developing conclusions. Students should be able to 1. Understand course readings 2. Apply material from course readings 1. Identify appropriate sources 2. Accurately cite and reference in APA-style 1. Utilize operational definitions Assessment Homework Poster & Project Presentations Poster & Project Presentations 1. Utilize multiple sources to develop a research hypothesis 2. Integrate results with previous research to draw conclusions Poster & Project Presentations 1. Properly evaluate the validity of research Exams, Quizzes, Homework - Students will analyze and interpret data appropriately. Students will evaluate the strengths and weaknesses of methods, theories, and/or evidence. RESEARCH METHODS IN PSYCHOLOGY SPRING 2022 Articulate Apply 2. Understand how features of research designs increase/decrease validity of research - Students will use scientific principles to solve problems. - Students will create an appropriate plan for post-graduate placement aligned with personal interests. O Students will communicate effectively in written form. 1. Communicate scientific information effectively Poster Students will communicate effectively in oral form. 1. Make formal presentations on scientific material. Presentations COURSE REQUIREMENTS (WHAT AM I REQUIRED TO DO IN THIS COURSE?) Reading Quizzes (12%): Each week is typically structured around a particular topic. The week will typically begin with an assigned reading from the text. For each of those reading assignments, students must complete a short quiz. This purpose of this is so that students are prepared for class, understanding the key features of the concepts covered. Students should carefully read the material before taking the quiz. Students must complete the quizzes on their own without the help of anyone else, except Dr. Albert (see Academic Honesty policy). The lowest quiz grades will be dropped at the end of the semester. Homework Assignments (10%): Each topic will often conclude with a homework assignment that addresses the material covered in the previous class(es). The assignments will be primarily questions about the material covered from the week. The due dates for homework assignments are provided in the Course Schedule; the questions and/or directions for each homework assignment are provided on Canvas. Format & Guidelines: Responses should be numbered and typed. All responses should fully, directly, and accurately answer the questions and should be written in your own words and supported by material from the textbook. Your answers should not be copied from the textbook. They should not be copied or supported from Internet sources; while there is a good deal of accurate information on the Internet, these sources are not helpful in answering specific questions because context matters a great deal in this course. Students must complete their homework on their own without the help of anyone except Dr. Albert. Failure to follow these guidelines will affect the accuracy of your answer and/or violate the academic honesty policy. Grading: Each submission will be evaluated for completeness (as supported by book content) and accuracy that demonstrates understanding of the material in your own words (see rubric below). As noted, your grade will be penalized for copying, paraphrasing, or utilizing content outside the textbook. Students lowest homework grade will be dropped at the end of the semester. Criteria Answer is complete, accurate, clear, and in students own words 10 = Excellent ALL criteria met w/NO weaknesses and/or omissions 8 = Good MOST criteria met w/LITTLE weaknesses and/or omissions 7= Moderate SOME criteria met w/SOME weaknesses and/or omissions 4 = Weak LITTLE criteria met w/MANY weaknesses and/or omissions 0 = No Score NO criteria met or no answer provided Exams (40%): There will be four (4) exams in the course, the last of which is comprehensive of the entire semester. Each exam, however, builds on previous material, so in some sense, each exam is cumulative. Grading: Each question will be assessed for accuracy, and the percentage of points earned will be the grade for the exam. Each exam is worth 10% of your final grade. Students final exam score will serve as the final exam grade and replace their lowest unit exam grade (i.e., Exams 1-3). In the event the students final exam grade is lower than their lowest grade on Exams 1-3, it will not replace any of those exam grades, but will only serve as their final exam grade. In either case, students will have 4 exam grades included in their final course grade; the final is not an optional, replacement-only exam. PAGE 2 OF 11 RESEARCH METHODS IN PSYCHOLOGY SPRING 2022 Posters (14%): An important feature of the research process is the communication of the scientific information. One of the primary ways to communicate scientific information is the development of conference-style posters. Students will develop two of these during the semesterone of which will report on a classdeveloped non-experimental design project, and the other will report on a student-developed experimental design project. Developing a conference poster consists of the design and format features, but most importantly, the content of the poster. Grading: A rubric will be used to evaluate the posters; this is available on Canvas. The content, format, and design of the first poster will be discussed in stages throughout the first project during class. This first poster will be submitted for a final grade worth 6% of your total grade. The second poster will be worth 8% of your total grade. Penalties will be applied to these grades if they are submitted late; see course policies. Note, these grades are separate from the presentation of the posters (see next section on presentations). Presentations (21%): A primary goal in this course is oral communication; specifically, the context of this course focuses on communicating scientific information. To address this, there are three (3) formal presentations across the semester (see below). Grading: The presentations will be evaluated with a rubric grading available on Canvas. Article Presentations (5% of your total grade): We will read several research articles throughout the class to serve as examples of and practice with the material. Small groups (~2-3 students) will be responsible for presenting the content of one of those articles to the class. The presenters should present the research as though they conducted the research. There should be a clear, linear narrative that has an engaging opening, a body containing a clear and accurate description of the articles purpose, hypothesis, method, and results, and a conclusion that links to the introduction and body. There should be a visual element supplements the talk and includes a figure or table developed by the presenters. The presenters should be able to address questions appropriate to the depth of material covered in the course up to that point. Final Draft Research Proposal (8% of your total grade): Groups of students will present a research Final Poster Project Report (8% of your total grade): The last presentation will be individual poster proposal for their group project that is supported by three empirical articles. This presentation should also include a step-by-step, detailed procedure for addressing the hypothesis. The proposed procedure for addressing this hypothesis should have appropriate measures that correspond to the variables in the hypothesis, be an appropriate design for testing the research hypothesis, and be absent of superfluous measures or steps. There should be a visual element that accompanies this presentation. presentation of the group project that explains the research hypothesis, method, measures, results, an appropriate evaluation of the work, and conclusions. Peer Evaluation (3%): An important part of the group project is acting as a good peer. This is part of ones professional behavior. As such, each member of your group will provide a rating of your performance that reflects your equal contribution, communication/contact with the group, etc. The percentage of points earned on these ratings will serve as your grade. A 5% penalty on the poster presentation will be administered if you fail to complete and/or submit the ratings of your group members on time. COURSE GRADES (HOW WILL GRADES BE DETERMINED IN THIS COURSE?) Each course requirement (e.g., homework, etc.) will be evaluated as detailed in the previous section. Your final grade is based on the weighted percentage of points with the following calculation adjustments: The lowest quiz grade and the lowest homework grade will be dropped from the final grade. Your final exam grade will also replace your lowest unit exam grade, as long as it is higher than one of the unit exam grades (Exams 1-3). Your grades are posted on Canvas. Final grades are not rounded-up or negotiated. The proportion of points for each grade level are provided in the following table: PAGE 3 OF 11 RESEARCH METHODS IN PSYCHOLOGY SPRING 2022 Grade A AB+ B BC+ % Points 93.0% to 100.00% 90.0% to <93.0% 87.0% to <90.0% 83.0% to <87.0% 80.0% to <83.0% 77.0% to <80.0% Grade C CD+ D DF % Points 73.0% to <77.0% 70.0% to <73.0% 67.0% to <70.0% 63.0% to <67.0% 60.0% to <63.0% <60.0% COURSE SCHEDULE (WHAT WILL BE REQUIRED EACH DAY?) Reading = textbook reading, indicates page numbers in textbook and assigned articles that are available (and numbered) on Canvas HW = homework assignment due by class time on the due date (unless otherwise noted) via Canvas submission Wed 5/11 @12:30-3:00pm): Final exam period. Per college policy, comprehensive exams are required to be taken during the scheduled time. Remote Start Instructions: As of 1-6-2022, the College plan is to hold classes in a remote manner from January 17-30; inperson classes are anticipated after this period. This class will meet live over Zoom (see link in canvas) during each scheduled meeting time. Students will be expected to have cameras on, and class participation expectations will be identical to those during in-person sessions. WK DATE THE DAYS TOPIC 1 1/17 Introduction to the Course 1/19 2 3 4 READING (textbook pages, not pdf pages) Course Syllabus pp. 25-27 ASSIGNMENT DUE DATES Introduction to Research pp. 28-35 Quiz 1 1/24 Theory to Hypothesis pp. 37-44 Article #1 HW: Article 1 Quiz #2 1/26 Ethics in Research pp. 63-70 1/31 Constructs to Operational Definitions pp. 87-90 & 102-106 Article #2 2/3 Construct Validity pp. 95-101 Quiz #5 2/7 Exam Review & Happiness Project (HP) Hypothesis Workshop Exam #1: Scientific Foundations + 2/9 5 2/14 7 Quiz #3 HW: Scientific Hypotheses Quiz #4 HW: Ethics and Article 2 HW: Exam 1 Review Exam 1 Submit Happiness measures Non-experimental designs Workshop: Developing a Method & Poster Survey Design HP: Survey Design MK Non-experimental chapter Article #3 HW: Poster background Quiz #6 pp. 184-202 Article #4 HW: Correlations Finalize surveys 2/21 Internal Validity HP: Data collection Quiz #7 Submit HP data 2/23 Experimental Designs HP: Data interpretation pp. 121-124 (to Within..) Article #5 Quiz #8 Between-Subjects Design Exam 2 Review HP: Poster creation Exam #2: Article #6 HW: IV and Between-subjects 2/16 6 HW: Complete Baseline Assessment Quiz by 4pm 2/28 3/2 pp. 113-119 & 128-129 (Internal Validity) SPRING BREAK PAGE 4 OF 11 HW: Unit 2 review Happiness Poster due Friday 3/4 RESEARCH METHODS IN PSYCHOLOGY SPRING 2022 WK 8 DATE THE DAYS TOPIC 3/14 Within-Subjects Designs Intro to Exp. Design (EP) Project Workshop: Exp project development 3/16 3/21 External Validity I: Measure to Measure 9 pp. 129-130 (External Validity) & 148 Article #9 3/28 Research Proposals Submit Slides via Canvas by 10AM 3/30 External Validity II: Samples & Populations 4/6 Samples & Populations (cont.) Exam Review Workshop: Posters : pp. 196-199 (to Conducting) Article #10 Exam 3: External Validity 4/13 Quasi-Experimental Research 4/18 EASTER BREAK 4/20 Complex Designs Workshop: Posters EP: Data analysis Pp. 221-236 Article #12 4/25 Mixed Designs Article #13 4/27 EP: Poster design Poster presentations handout 5/2 Poster Presentations 5/3 5/4 Department Poster Session @11am Poster Presentations, Exam Review Wed 5/11 @12:30-3:00pm Quiz #9 Quiz #10 HW: Literature Review HW: Submit Research Hypothesis Outline Research Proposal Presentation Quiz #11 HW: Samples HW: Exam 3 review 4/11 13 16 HW: Within Article #8 11 15 Draft Research Proposal Meetings 4/4 14 ASSIGNMENT DUE DATES 3/23 10 12 READING (textbook pages, not pdf pages) pp. 124-127 Article #7 MK Quasi Chapter Article #11 Quiz #12 Data due by Friday 4/15 at 10am HW: Quasi- experiments Quiz 13 HW: Factorials Poster Due on Friday (4/29) @10AM Individual Presentations ----------- Exam #4: Quasi-& Complete Experiments + Comprehensive Final Exam HW: Exam 4 review Peer Evaluations Due ----------- COURSE PRINCIPLES & POLICIES (WHAT ARE THE EXPECTATIONS AND GUIDELINES FOR THIS COURSE?) Attendance Policy: It is expected that students will be prepared for each class having completed the assigned reading in advance and be prepared to actively contribute to the discussion. This course involves the synthesis of a good number of primary sources. Please have your typed HW answers available during class sessions and expect to contribute your answers when called on. Missed/Late Work Policies: All course work (assignments, exams, etc.) are to be completed on time and submitted as specified. Late work, missed assignments, and/or work not submitted appropriately will not be accepted for credit; those assignments will receive a zero. o Students lowest homework grade and lowest quiz grade will be dropped from the final grade calculations. These no-penalty missed assignments provides flexibility for various situations that prevent students from completing work on time. PAGE 5 OF 11 RESEARCH METHODS IN PSYCHOLOGY SPRING 2022 There are no make-up exams. Students final exam score will serve as the final exam grade and replace their lowest unit exam grade (i.e., exams 1-3) as long as the final exam grade is higher than one of the unit exam grades. Thus, the final exam grade would replace a missed unit exam. o For presentations, students should switch with another student who agrees to do so, and in extremely rare cases, an alternative version of the assignment may need to be considered, where there are legitimate, documented excuses (primarily limited to school function, sickness requiring doctor or hospital). In the event that presentations or posters or other work associated with the presentations are late, penalties will be applied as follows: 5% up to 2-hours late, 10% after 2-hours, 15% after 12-hours, and those submitted after 24-hours will receive a zero. o In the typical case of sickness or need for quarantine, students should complete and submit their work on time. In the event that there is a legitimate, documented, long-term situation that prevents students from completing the course work, we will negotiate appropriate due dates, but students should not expect this as a regular practice for all situations and/or any degree of illness. If a students personal circumstances prevent them from completing a large portion of the class (more than a week), it may be good to consider the pass/fail or drop options. Academic Honesty Policy: The colleges academic honesty code at the college applies to this class. In short, all workincluding homework and quizzesshould be completed without the aid of anyone else unless it is specifically assigned as collaborative work, nor should students use the Internet or online aids (e.g., bartleby) to look up answers. Any violation of any part of this policy (including those policies about academic honesty outlined in the colleges student handbook) will result in a minimum of a zero on the work involved in the violation. o This syllabus was created by Rachel Albert and Michael Kitchens, Support for the project was generously provided by the Pennsylvania Grants for Open and Affordable Learning (PA GOAL) program, Grant #40. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License and may not be reproduced for commercial purposes. Appendix A. Reading list Article #1: Diener, E., & Seligman, M. E. P. (2002). Very Happy People. Psychological Science, 13(1), 8184. https://doi.org/10.1111/1467-9280.00415 Article #2: Schiffrin, H. H., & Nelson, S. K. (2010). Stressed and happy? Investigating the relationship between happiness and perceived stress. Journal of Happiness Studies: An Interdisciplinary Forum on Subjective Well-Being, 11(1), 3339. https://doi.org/10.1007/s10902-008-9104-7 Article #3: Mehl, M.R., Vazire S., Holleran, S.E., & Clark C.S. (2010). Eavesdropping on Happiness: Well-being is related to having less small talk and more substantive conversations. Psychological Science, 21(4), 539541. https://doi.org/10.1177/0956797610362675 Article #4: Rozin, P., Kabnick, K., Pete, E., Fischler, C., & Shields, C. (2003). Ecology of eating: Smaller portion sizes in France than in the United States help to explain the French paradox. Psychological Science, 14(5), 450-454. https://doi.org/https://doi.org/10.1111/1467-9280.02452 PAGE 6 OF 11 RESEARCH METHODS IN PSYCHOLOGY SPRING 2022 Article #5: OBrien, E., & Ellsworth, P. C. (2012). Saving the last for best: A positivity bias for end experiences. Psychological Science, 23(2), 163165. https://doi.org/10.1177/0956797611427408 Article #6: Pennycook, G., McPhetres, J., Zhang, Y., Lu, J. G., & Rand, D. G. (2020). Fighting COVID-19 Misinformation on Social Media: Experimental Evidence for a Scalable Accuracy-Nudge Intervention. Psychological Science, 31(7), 770780. https://doi.org/10.1177/0956797620939054 Article #7: Hagemann, N., Strauss, B., & Leiing, J. (2008). When the referee sees red . Psychological Science, 19(8), 769771. https://doi.org/10.1111/j.1467-9280.2008.02155.x Article #8: Sobel, H.S., Cepeda, N.J. & Kapler, I.V. (2011). Spacing effects in real-world classroom vocabulary learning. Applied Cognitive Psychology, 25, 763-767. https://doi.org/10.1002/acp.1747 Article #9: Nelson, L. D., & Simmons, J. D. (2007). Moniker maladies: When names sabotage success. Psychological Science, 18(2), 1106-1112 https://doi.org/10.1111/j.1467-9280.2007.02032.x Article #10: Norton, M. I., & Ariely, D. (2011). Building a better America--One wealth quintile at a time. Perspectives on Psychological Science, 6(1), 9-12. https://doi.org/10.1177/1745691610393524 Article #11: Barya, W., & Wojciszke, B. (2019). Success leads to agentic cognition: Two field studies. Social Psychological and Personality Science, 10(3), 402408. https://doi.org/10.1177/1948550618765065 Article #12: Donnelly, G. E., Zatz, L. Y., Svirsky, D. & Leslie J. K. (2018). The effect of graphic warning on sugary drink purchasing. Psychological Science, 29(8), 1321-1333. https:doi.org/101177/09567976187663661 [read through Study 1 only] Article #13: Strayer, D. L., & Johnston, W. A. (2001). Driven to distraction: Dual-task studies of simulated driving and conversing on a cellular phone. Psychological Science, 12, 462-466. DOI: 10.1111/1467-9280.00386 PAGE 7 OF 11 RESEARCH METHODS IN PSYCHOLOGY SPRING 2022 APPENDIX B. LVC Institutional Policies that apply to this course Policy on Recording Class Sessions Audio and/or video recordings of the class sessions may be made by the College and/or by students who have been authorized by the LVC Center for Accessibility Resources to record classes as an accommodation for a disability. By participating in the class, all students consent to being recorded for these purposes. Any other recordings of class sessions are not permitted. Students participating in on-line courses are asked to respect the privacy of those participating in the class by ensuring that class sessions cannot be overheard by those who are not enrolled in the course. Academic Honesty Policy Any student who submits plagiarized work will be subject to the penalties described in the Student Handbook and the College Catalog and outlined in LVCs Academic Honesty Policy. (https://www.lvc.edu/academics/academic-resources/college-catalogue/college-academic-policies-andprocedures/academic-honesty/) This code asks each student to do his/her own work in his/her own words. A student shall neither hinder nor unfairly assist the efforts of other students to complete their work. All individual work that a student produces and submits as a course assignment must be the students own. Cheating and plagiarism are acts of academic dishonesty. Cheating is an act that deceives or defrauds. It includes, but is not limited to, looking at anothers exam or quiz, using unauthorized materials during an exam or quiz, colluding on assignments without the permission or knowledge of the instructor, and furnishing false information for the purpose of receiving special consideration, such as postponement of an exam, essay, quiz or deadline of an oral presentation. Plagiarism is the act of submitting as ones own, the work (the words, ideas, images, or compositions) of another person or persons without accurate attribution. Plagiarism can manifest itself in various ways: it can arise from sloppy note-taking; it can emerge as the incomplete or incompetent citation of resources; it can take the form of the wholesale submission of other peoples work as ones own, whether from an online, oral or printed source. Students who take part in violations such as cheating or plagiarism are subject to a meeting with the Assistant Dean and Director of Constellation, who has the authority to take further action, up to and including expulsion from the College. Unicheck Policy In this course you may be asked to submit some or all of your assignments for review by an online plagiarism service. This service will compare the content of your work to content found on the internet and several proprietary databases. Any work submitted to this service may become part of the services permanent collection of submitted papers. After your work is submitted, the service will generate an originality report, which will be sent to your instructor. Any student who submits plagiarized work will be subject to the penalties outlined in LVCs Academic Honesty Policy found in the Student Handbook and the College Catalog. https://www.lvc.edu/offices-directories/information-technology/educationaltechnology-resources/unicheck/ PAGE 8 OF 11 RESEARCH METHODS IN PSYCHOLOGY SPRING 2022 End of Term Course Evaluations Most courses at the College utilize a course evaluation system called EvaluationKIT. Near the end of the term, you will have the opportunity to evaluate the course in a number of key areas: learning environment, instructor performance, overall course structure, progress on relevant course objectives, and Constellation learning outcomes (if they apply). The faculty have approved a set of common questions that students will respond using an agreement scale. Please note that quantitative survey results and comments are used for course and instructor improvements and to indirectly measure the progress on relevant student learning objectives. Policies Regarding Accessibility Resources Policies Regarding Students with Disabilities Individuals with disabilities are guaranteed certain protections and rights of equal access to programs and activities under Section 504 of the Rehabilitation Act of 1973 and the Americans with Disabilities Act Amendments Act (ADAAA) of 2008. Therefore, Lebanon Valley College recognizes the responsibility of the college community to provide equal educational access for otherwise qualified students with disabilities. In-Person and Online Courses: Any student who needs accommodations is invited to provide letters from the Center for Accessibility Resources and discuss accommodations with me. Any student who feels they may need accommodations based on a documented disability or other condition that may affect academic performance should: contact The Center for Accessibility Resources, located in the Lebegern Learning Commons Mund Suite 002. Students may schedule an appointment by calling 717-867-6028 or emailing hannafor@lvc.edu to determine if accommodations are warranted and to obtain an official letter of accommodation. Assistive Technology is available to enhance your academic skills. The Center for Accessibility Resources, located in the Lebegern Learning Commons Mund Suite 002, offers educational software and personal assistive devices for short-term loans. Available assistive devices include LiveScribe pens, mini iPads, digital recorders, headphones, and adaptive keyboards. Our student coordinator is available to meet with students throughout the semester to suggest devices and/or software aligned to individual student needs. If a student believes that appropriate accommodations are being denied, the student may file a grievance. Procedures for filing grievances may be found at https://www.lvc.edu/offices-directories/center-foraccessibility-resources Statement on Inclusive Excellence LVC is a community of inclusive excellence. We affirm the rights of all persons to a superior educational experience that is characterized by respect for others. As such, this class and all classes at LVC, are places where our core values of inclusiveness, civility and appreciation of difference are affirmed. Policy on Preferred Names and Pronouns Lebanon Valley College is committed to fostering an environment of inclusion and support, which includes honoring all its members forms of self-identification. This policy provides uses of preferred first names and pronouns for students, faculty, staff, friends, and alumni who wish to provide them. Many PAGE 9 OF 11 RESEARCH METHODS IN PSYCHOLOGY SPRING 2022 members of the LVC community may use names other than their legal names to identify themselves. If the use of this different name is not for misrepresentation, LVC acknowledges that a preferred name may be used wherever possible. The preferred name will be recorded and used except where the legal name is required. Although students, faculty, staff, friends, and alumni are free to determine the preferred name and pronoun they wish to be known by, the College deserves the right to deny a preferred name and pronoun if it is used inappropriately. Gender pronouns are those pronouns that members of the community use to represent themselves. Gender pronouns can include, but are not limited to, he/him/his, she/her/hers, they/them/theirs, etc. Asking for and correctly using a persons pronoun is one of the most basic ways to show respect for a persons gender identity. Preferred name and pronouns will be entered and accessible internally for members of the campus community. Lebanon Valley College expects all faculty, staff, and students to facilitate the use of preferred names and pronouns listed on the directory and class rosters. Title IX Statement Lebanon Valley College prohibits discrimination on the basis of race, color, national origin, ancestry, religion/creed, sex, pregnancy, sexual orientation, gender identity or expression, age, disability, genetic information, marital/familial status, or veteran status in all programs and activities, as required by Title IX of the Educational Amendments of 1972, the Americans with Disabilities Act of 1990, Section 504 of the Rehabilitation Act of 1973, Title VII of the Civil Rights Act of 1964, and other applicable statutes and/or College policies. Lebanon Valley College prohibits discriminatory harassment and sexual harassment, including sexual violence and any type of sexual misconduct. Title IX makes it clear that violence, harassment, and any type of sexual misconduct based on sex and gender are civil rights violations. If you or someone you know has experienced violence, discrimination, or harassment, support is available through Counseling Services, Health Service, the Chaplains office, and Title IX deputies. Please refer to the Student Handbook or the College Catalog for specific contact information. Policy on Student Success and Intervention Starfish Starfish is an online tool used at LVC that gives you the opportunity to connect with faculty and staff to cultivate your success. Through Starfish, you can submit concerns, access beneficial resources, connect with your Success Network, and receive updates on your academic progress. This tool also allows faculty and staff to recognize when you might need extra help and reach out to collaboratively resolve an issue. If you receive a Starfish Flag showing that someone has a concern, you will receive an email with a specific action plan to follow. Take that action and work with us to maximize your success. CARE Team At Lebanon Valley College, we want you to succeed in and out of the classroom. Administrators and faculty work together on the CARE Team to cultivate Confidence, Accountability, Resilience, and Engagement in every student. If a member of the LVC community is concerned about you for any reason (i.e. academic, social, or emotional issues), they will ask a CARE team member to reach out to you and work with you towards a solution. You should consider it your assignment to follow through and accept PAGE 10 OF 11 RESEARCH METHODS IN PSYCHOLOGY SPRING 2022 assistance from the appropriate source(s). Dont be afraid or hesitant to seek help from these individuals: supporting you is their job! Be proactive and take control of your success. The Center for Academic Success and Exploratory Majors Located in the lower-level of Mund College Center, the Center for Academic Success serves to support, inspire, and cultivate student success. The key to performing well academically lies in frequently utilizing support services across campus; in fact, many of our top students utilize tutors to help prepare for exams, talk through challenging concepts, learn how to take effective notes, and more. For this reason, we staff over nearly 300 peer tutors in almost all 100 and 200-level classes, including subject-specific writing conferencing. We also offer weekly study groups called "Study Pods" for specific subjects that serve as a place to connect with classmates, ask questions, and work on homework as well as drop-in writing support from 7pm-9pm, Mondays through Thursdays. If you would like to work with a tutor, please fill out a tutor request form (also located on the CASEM website). In addition, the Center features academic success coaching, where staff members support students by designing and implementing a plan for academic success. These "coaching" sessions focus on developing effective time management, organizational, test-taking, critical reading, note-taking, and study skills, as well as learning healthy behavioral techniques like stress management and self-motivation. . For more information on any of these services, visit the Center for Academic Success. To request an appointment, please email findyoursuccess@lvc.edu. The Center also serves as the home on campus to Exploratory (undecided) majors. Statement on Supporting Mental Health Counseling Services Your mental health, including excessive stress, anxiety, depression or problems with eating and/or sleeping can adversely influence your academic performance. At LVC we care about the whole person. If you feel that any of these issues are negatively impacting your performance, please contact our Counseling Services to consult with one of our professional counselors. During a brief phone conversation, they can assess your particular needs and help you make a connection to the services you may need. If you would like a phone consultation, just email counselingservices@lvc.edu and leave your contact information. A professional counselor will return your call or email the next business day. We will not check email after hours or over the weekend/vacation times. If you experience an emergency, please call 911 in your local area or text 741741 to request immediate assistance. Many students report that starting the counseling process earlier in the semester has taught them important coping skills that helped improve their academics. Click here to explore all Counseling Services has to offer. PAGE 11 OF 11  ...

... DS 201 Introduction to Data Science Fall 2021 Course Schedule: MW, 3:004:15, Loyola Science Center (LSC) 316. Instructor: Joe Klobusicky (joseph.klobusicky@scranton.edu, LSC 211E) Office Hours: Mondays 4:30-5:30, Thursdays 3:00-5:00 in LSC 211E, or by appointment. Overview: Data science has steadily made its way into almost every field of science and industry. From computational finance to medicine to retail, careers are depending more and more on the analysis of data. Since this is such a new phenomenon, its somewhat hard to give a precise definition of data science, since it means different things to different people. For this class, we will cover fundamentals associated with handling data. Certainly this will include some time on visualizing data, but perhaps more important is an understanding of what a good visualization actually means. This means that we will spend a large chunk of the class giving a lightning quick introduction to interpreting data through probability and statistics. We will also take our new understanding of these fields for a test drive, and look at some of machine learnings greatest hits, including k-nearest neighbors and k-means for classification and prediction problems. At the end of the course, you should have a working knowledge for what data science is, and hopefully an idea of what classes you should take to further your studies into this highly popular discipline. Course Web Site: We will be using D2L for submitting homework and keeping track of grades. Texts: The main text used in this course will be open source notes found at https://scrantondatanotes.netlify.app These notes have the following creative commons license: Text and figures are licensed under Creative Commons Attribution CC BY-NC 4.0. The figures that have been reused from other sources dont fall under this license and can be recognized by a note in their caption: Figure from . . . . Along with these notes, there will be plenty of other required texts, articles, and tutorials, all of which will be made available as the semester progresses. Outline and Text Reading: The following is the tentative schedule for topics covered. Sections in parentheses will be covered, time permitting. 1. Getting started. R and RStudio, importing/exporting data. 2. Basic programming in R. Loops, functions. 3. Looking at data. Exploratory Data Analysis and Data Visualization. Data cleaning. 4. Crash course in probability and statistics. p-values from a permutation perspective. After taking this course, the student should be able to: 1. Import, clean, and visualize data 2. Understand data from a probabilistic and statistical lens 3. Use regression and clustering methods for predictive modeling. Methods of assessment Homework Homework Homework 5. Basic Modeling. Regression in its various flavors, smoothing, penalized regression. 6. Data science algorithms. Clustering. k-nearest neighbors and k-means. 7. Time permitting, more topics in machine learning. Web-scraping and text algorithms, neural networks. Course Goals: The goal of this course is for students 1. to gain fundamental skills in data visualization and interpretation, including proper data visualization and statistical analysis including hypothesis testing. 2. to implement informative modeling through both classical regression methods and more modern machine learning algorithms. Student Learning Objectives and Assessment: Grading Policy: Take home assignments for 100% of course grade. These will be approximately biweekly (once every two weeks), and about six assignments will be given. Since this is essentially the only point of evaluation, homeworks will be quite thorough and difficult! Make sure to spend significant time on the homework. Homework policy: Homework is due at 5:00 pm on the due date by uploading on D2L. I will not accept hard copies of homework. Late homework is a very bad idea. You may hand in your homework one day late at a 50% penalty. After that, homework will not be accepted. If you feel that you need an extension, please speak to me as soon as possible. Your request may be denied, but there is no penalty in asking. There is very much a penalty, however, for not submitting homework and then providing excuses after the due date or the night it is due. That kind of behavior can get you fired from a job, so it will not be tolerated in this class. You may work with others, but you are never allowed to copy another students work. In particular, your code and the rest of your solutions must be written yourself. Identical solutions will result in a score of 0 for all parties involved. If youre concerned whether your submission is plagiarism, just ask me before you hand in your assignment. Again, theres no penalty for asking! A very important point: start homework early. If you begin the night before, you are bound to produce drivel. Many questions in the homework require a great deal of thought, and you will almost certainly find yourself getting stuck for several days at a time. If things get confusing to you, please utilize office hours or just send me an email. Remember, for office hours, I dedicate three hours every week in which your questions take priority in my queue of things to do. These are your hours! Academic Integrity: All matters involving academic integrity will be taken very seriously. The breach of trust between a student and teacher is a disservice to University of Scranton faculty, students, and alumni. The University of Scranton lays out its standards in its Academic Code of Honesty and you should make yourself familiar with this. Among other violations laid out in the Academic Code, copying from fellow students work is a serious breach of academic integrity. If caught, you will be sent to the Dean with the recommendation that you be expelled from the class with a failing grade. Standard University procedure for other academic integrity breaches will be followed. Syllabus revision: In the event of a change of class modality (in class to online, in class to hybrid, etc.), or for any other reason, I reserve the right to change syllabus policy, including grading procedures. You will be notified if any such changes occur.  ...

... 5/2/22, 1:36 PM MATH 204 (Q) Introduction to Statistics Instructor Information: Course Materials: Course Information: Course Policies and Procedures: Course Timeline: University Resources for Students and Academic Honesty: MATH 204 (Q) Introduction to Statistics Instructor Information: Instructor: Dr. Jason M. Graham Office: 319A LSC Office Hours: Mondays and Thursdays 1:30 - 3:30 PM (You may also make an appointment to meet with me outside of scheduled office hours. Appointments are not necessary for regularly scheduled office hours.) Dr. Grahams Schedule: Link (https://www.dropbox.com/s/zp1bg5stofbrvjk/FALL%202021%20Schedule%20JMG.pdf?dl=0) Email: jason.graham@scranton.edu (mailto:jason.graham@scranton.edu) Phone: (570) 941-7491 Course Materials: Required Textbook The required textbook for this course is OpenIntro Statistics (https://www.openintro.org/book/os/) 4th edition which is freely available online at the link provided. Additionally, print copies are available for a low cost. Additional Resources: The textbook website (https://www.openintro.org/book/os/) provides access to additional resources such as lectures videos, slides, etc. Students are encouraged to make use of these resources. Other valuable resources include 1. Learning Statistics with R (https://learningstatisticswithr.com/) (see also the well-produced online version (https://learningstatisticswithr.com/book/)). This book will serve as our supplementary reference for using the R language (https://www.r-project.org/) for statistical https://math204fall2021.netlify.app/syllabus.html 1/9 5/2/22, 1:36 PM MATH 204 (Q) Introduction to Statistics computing. 2. Elementary Statistics with R tutorials (http://www.r-tutor.com/elementary-statistics) 3. Elementary Statistics with R online book (https://homerhanumat.github.io/elemStats/) Course Information: Course Description Study of the computational aspects of statistics; hypothesis testing, goodness of fit; nonparametric tests; linear and quadratic regression, correlation and analysis of variance. Not open to students who have credit for or are enrolled in an equivalent statistics course. Prerequisites It is recommended that students enrolled in MATH 204 be comfortable in carrying out addition, subtraction, multiplication, and division of decimal and fraction numbers. Course Goals The goals for this course are for students to: understand the features and structures of data appropriate for basic statistical investigation, learn to gain insight from appropriate data by the methods of statistics at the introductory level, gain experience in working with data and performing statistical analyses at the introductory level, and obtain a firm understanding of the notion of sampling distribution (https://en.wikipedia.org/wiki/Sampling_distribution) as appropriate at the introductory level. Student Learning Objectives and Assessment After taking this course, the student should be able to: Methods of assessment Work with data: identify variables as categorical, discrete, or continuous; describe basic techniques of data collection and sampling; explain and interpret basic numerical and graphical data summaries. Concept quizzes, homework, labs, and exams. Work with probability distributions and random variables at an introductory level. Concept quizzes, homework, labs, and exams. Explain the concept of sampling distribution. Concept quizzes, homework, labs, and exams. Conduct and interpret basic statistical inferences. Concept quizzes, homework, labs, and exams. Link with Mathematics Program Learning Outcomes The student learning objectives of this course are linked with the Mathematics Program Learning Outcome Demonstrate competence in analytical and critical reasoning. https://math204fall2021.netlify.app/syllabus.html 2/9 5/2/22, 1:36 PM MATH 204 (Q) Introduction to Statistics Link with General Education Goals and Objectives As a course with a general education (GE) quantitative reasoning designation (Q), the student learning objectives of this course are linked with the following GE goals and objectives: Students will demonstrate analytic reasoning and critical thinking within and across disciplines. Use mathematical, quantitative or statistical models (i.e., ones based on an axiomatic system) for concrete or abstract problem solving or decision making. Course Policies and Procedures: COVID Safety Pertaining to the Course In consideration of the care and concern for one another and members of our community, unless you are reasonably unable to do so, please take the following steps as a student in this course to mitigate the spread of coronavirus: 1. Do not attend class if you have a confirmed case of coronavirus disease (COVID) until you have fully recovered. 2. Do not attend class if you are experiencing any COVID related symptoms as described at this link (https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html). 3. Do not attend class if you believe that you have been exposed to the coronavirus and might spread it to members of the class. Please visit this link (https://www.cdc.gov/coronavirus/2019ncov/transmission/index.html) for information on the transmission of the coronavirus. 4. Wear a CDC approved face covering (https://www.cdc.gov/coronavirus/2019-ncov/preventgetting-sick/diy-cloth-face-coverings.html) over your mouth and nose while in the classroom and while visiting the course instructors office. Attendance It is important that you attend class regularly. If you must miss class for any reason notify the instructor as soon as possible to make arrangements to quickly make up any content missed by absence. Assignments and Grading: Grade Policy The course grade will be based on regular concept quizzes (15%), participation (15%), homework (15%), bi-weekly labs (15%), one mid-term exam (20%), and a final exam (20%). Grade Scale Letter grades will be assigned based on the following scale: https://math204fall2021.netlify.app/syllabus.html 3/9 5/2/22, 1:36 PM MATH 204 (Q) Introduction to Statistics Grade Range Letter Grade 94-100 A 90-93 A- 87-89 B+ 83-86 B 80-82 B- 76-79 C+ 72-75 C 69-71 C- 65-68 D+ 60-64 D <60 F Concept Quizzes In this course students will be asked to complete a number of concept quizzes. Concept quizzes are meant to be a quick check that you are following the lectures and textbook readings. These quizzes will be timed and administered via the course learning management system (D2L), and the concept quizzes will be given after most class meetings. Participation For the purpose of this course, participation means actively engaging in the course both inside and outside of the classroom and taking individual ownership of learning. Note that participation is not limited to what is often meant by in-class participation. Students will be asked to complete a number of participation assignments, these assignments will usually take the form of a small number of prompts to which students will be asked to respond. Homework Labs and exams will build on practice problems so it is essential to complete homework practice problems in preparing for quizzes and labs. Do not underestimate the value (and joy) of carefully working through homework problems. Labs The bi-weekly lab assignments for this course are meant to assess your developing skills in working with data and conducting analyses using R. Some labs will be in-class while others may be assigned as homework. All labs will be done with RStudio cloud (https://rstudio.cloud/) using templates set up by the instructor and accessed via a shared link. Exams https://math204fall2021.netlify.app/syllabus.html 4/9 5/2/22, 1:36 PM MATH 204 (Q) Introduction to Statistics The mid-term and final exams are meant to assess 1) students understanding of the material covered in class and in assignments, 2) students understanding of the core concepts, 3) students problem solving abilities, and 4) students ability to think independently. In order to encourage active participation in the learning process, the instructor invites all students to submit suggested problems to appear on each exam. The rules are as follows: On any given exam, any individual student is welcome to submit up to two problems for consideration. Submissions must be made a minimum of three days before the exam for which they are to be considered. Along with a clear statement of the problem must appear a carefully, clearly, and correctly written solution. Any problem submission, along with the solution, will be copied and handed out to the rest of the class at least one day before the exam. Students will not know in advance if their problem has been chosen to appear on the exam. Note: The instructor is under no obligation to use any or all of the submitted problems. However, the more problems that students submit, the greater the chances that some will be chosen to appear on an exam. Course Timeline: Important Dates Event Date Classes begin Monday, August 30 Last day to add classes Friday, September 3 Labor day, no classes Monday, September 6 Last day for 100% tution refund Wednesday, September 8 Last day to drop with no grade Wednesday September 29 Last day of class before fall break Friday, October 8 Classes resume after fall break Wednesday, October 13 Mid-term exam Thursday, October 14 Semester Midpoint Friday, October 15 Last day to withdraw with W grade Friday, November 12 Last day of class before Thanksgiving break Tuesday, November 23 Classes resume after Thanksgiving Monday, November 29 Last day of class Monday, December 13 Final exams begin Tuesday, December 14 Final exams end Saturday, December 18 Weekly Schedule Week 1: Intro to Data, Sampling, and Intro to R https://math204fall2021.netlify.app/syllabus.html 5/9 5/2/22, 1:36 PM MATH 204 (Q) Introduction to Statistics Week 2: Data summaries, Visualization Week 3: Intro to Probability, Random variables Week 4: Probability distributions Week 5: Normal distribution, Foundations for inference Week 6: Inference for proportions Week 7: Mid-term exam Week 8: Goodness of fit Week 9: Inference for numerical data, One-sample tests Week 10: Paired data, Power Week 11: ANOVA Week 12: Intro to regression Week 13: Regression inference Week 14: Multiple and nonlinear regression Week 15: Additional topics University Resources for Students and Academic Honesty: Students with Disabilities Reasonable academic accommodations may be provided to students who submit relevant and current documentation of their disability. Students are encouraged to contact the Center for Teaching and Learning Excellence (CTLE) at disabilityservices@scranton.edu (mailto:disabilityservices@scranton.edu) or (570) 941-4038 if they have or think they may have a disability and wish to determine eligibility for any accommodations. For more information, please visit http://www.scranton.edu/disabilities (http://www.scranton.edu/disabilities). Writing Center Services The Writing Center focuses on helping students become better writers. Consultants will work one-onone with students to discuss students work and provide feedback at any stage of the writing process. Scheduling appointments early in the writing progress is encouraged. To meet with a writing consultant, call (570) 941-6147 to schedule an appointment, or send an email with your available meeting times, the course for which you need assistance, and your phone number to: writing-center@scranton.edu (mailto:writing-center@scranton.edu). The Writing Center does offer online appointments for our distance learning students. Please contact Amye Archer at amye.archer@scranton.edu (mailto:amye.archer@scranton.edu) for more information. Academic Honesty and Integrity Each student is expected to do their own work. It is also expected that each student respect and abide by the Academic Code of Honesty as set forth in the University of Scranton student handbook. Conduct that violates the Academic Code of Honesty includes plagiarism, duplicate submission of the same work, collusion, providing false information, unauthorized use of computers, theft and destruction of property, and unauthorized possession of tests and other materials. Steps taken in response to https://math204fall2021.netlify.app/syllabus.html 6/9 5/2/22, 1:36 PM MATH 204 (Q) Introduction to Statistics suspected violations may include a discussion with the instructor, an informal meeting with the dean of the college, and a hearing before the Academic Dishonesty Hearing Board. Students who are found to have violated the Code will ordinarily be assigned the grade F by the instructor and may face other sanctions. The complete Academic Code of Honesty is located on the University website at https://www.scranton.edu/academics/wml/acad-integ/acad-code-honesty.shtml (https://www.scranton.edu/academics/wml/acad-integ/acad-code-honesty.shtml). My Reporting Obligation as a Responsible Employee As a faculty member, I am deeply invested in the well-being of each student I teach. I am here to assist you with your work in this course. Additionally, if you come to me with other non-course-related concerns, I will do my best to help. It is important for you to know that all faculty members are required to report incidents of sexual harassment or sexual misconduct involving students. This means that I cannot keep information about sexual harassment, sexual assault, sexual exploitation, intimate partner violence or stalking confidential if you share that information with me. I will keep the information as private as I can but am required to bring it to the attention of the Universitys Title IX Coordinator, Elizabeth M. Garcia, or Deputy Title IX Coordinator, Christine M. Black, who, in conversation with you, will explain available support, resources, and options. I will not report anything to anybody without first letting you know and discussing choices as to how to proceed. The Universitys Counseling Center (570941-7620) is available to you as a confidential resource; counselors (in the counseling center) do not have an obligation to report to the Title IX Coordinator. Non-discrimination Statement The University is committed to providing an educational, residential, and working environment that is free from harassment and discrimination. Members of the University community, applicants for employment or admissions, guests, and visitors have the right to be free from harassment or discrimination based on race, color, religion, ancestry, gender, sex, pregnancy, sexual orientation, gender identity or expression, age, disability, genetic information, national origin, veteran status, or any other status protected by applicable law. Students who believe they have been subject to harassment or discrimination based on any of the above class of characteristics, or experience sexual harassment, sexual misconduct or gender discrimination should contact Elizabeth M. Garcia, Title IX Coordinator, (570) 941-6645 elizabeth.garcia2@scranton.edu (mailto:elizabeth.garcia2@scranton.edu), Deputy Title IX Coordinators Christine M. Black (570) 941-6645 christine.black@scranton.edu (mailto:christine.black@scranton.edu), or Ms. Lauren Rivera, AVP for Student Life and Dean of Students, at (570)941-7680 lauren.rivera@scranton.edu (mailto:lauren.rivera@scranton.edu). The United States Department of Educations Office for Civil Rights (OCR) enforces Title IX. Information regarding OCR may be found at The University of Scranton Sexual Harassment and Sexual Misconduct Policy can be found online at https://www.scranton.edu/diversity (https://www.scranton.edu/diversity). All reporting options and resources are available at https://www.scranton.edu/CARE (https://www.scranton.edu/CARE). About Pronouns https://math204fall2021.netlify.app/syllabus.html 7/9 5/2/22, 1:36 PM MATH 204 (Q) Introduction to Statistics It is easy to make assumptions about what pronouns people prefer, but we try not to! Please tell us in class or via a private email if you would like to let us know what your pronouns are, if/when you would like us (and others) to use them, and certainly feel free to correct us or others if we make a mistake. Using the pronouns that a person has indicated they prefer is considered both professional and polite, and as such we ask that all members of our class use the appropriate pronouns. If you have questions about this, please feel free to look up more information here (https://www.mypronouns.org/ (https://www.mypronouns.org/)) or email jason.graham@scranton.edu (mailto:jason.graham@scranton.edu) with any questions. License This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) (https://creativecommons.org/licenses/by-nc-sa/4.0/). This is a human-readable summary of (and not a substitute for) the license. Please see https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode) for the full legal text. You are free to: Share copy and redistribute the material in any medium or format Adapt remix, transform, and build upon the material The licensor cannot revoke these freedoms as long as you follow the license terms. Attribution You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. NonCommercial You may not use the material for commercial purposes. ShareAlike If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original. No additional restrictions You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits. Notices: You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation. No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material. Final Note The instructor reserves the right to modify this syllabus; students will immediately be notified of any such changes and an updated syllabus will be made available to the class via the course learning management system. https://math204fall2021.netlify.app/syllabus.html 8/9 5/2/22, 1:36 PM https://math204fall2021.netlify.app/syllabus.html MATH 204 (Q) Introduction to Statistics 9/9  ...