{"panels":[{"content":{"params":{"text":"

FACULTY OF EDUCATION<\/h2>\n\n
401 Sunset Avenue, Windsor, Ontario, Canada N9B 3P4
\nTel: (519) 253-3000 ext. 3800 Fax: (519) 971-3694<\/p>\n\n

EDUC 8100: STATISTICS IN EDUCATION<\/h2>\n\n

Winter 2021 Course Outline<\/h2>\n\n
<\/p>\n\n
Class Time: See Tentative Schedule for Days and Times of Synchronous Sessions, Learning Module Release Dates, and Virtual Individual Drop-In Sessions<\/p>\n\n
Dates: January 10, 2021 \u2013 April 10, 2021<\/p>\n\n
Study Week: February 13 \u2013 20, 2021<\/p>\n\n
<\/p>\n\n
Location: ON-LINE<\/p>\n\n
Instructor: Dr. R. D. Stanley<\/p>\n\n
Office: Virtual Classroom on Course BlackBoard Site<\/p>\n\n
Office Hours: Please email to set up an appointment<\/p>\n\n
E-Mail: dstanley @ uwindsor.ca<\/a><\/p>\n\n
Course Website: blackboard.uwindsor.ca<\/a><\/p>\n\n
<\/p>\n\n
* NOTE: All information herein is subject to change in response to changes in contextual variables and participant learning needs.<\/p>\n"},"library":"H5P.AdvancedText 1.1","subContentId":"2c954d64-7aa4-4fc5-a556-17d5f1eb0d98","metadata":{"contentType":"Text","license":"U","title":"Untitled Text"}},"title":"COURSE CONTACT INFORMATION"},{"content":{"params":{"text":"
This course will deal with the following: descriptive and inferential statistical procedures; commonly used one- and two-sample tests; an introduction to analysis variance and corresponding research designs. (3 hours a week.)<\/em><\/em><\/p>\n"},"library":"H5P.AdvancedText 1.1","subContentId":"6429acb9-d071-42fd-b4b5-486fb5c62ec8","metadata":{"contentType":"Text","license":"U","title":"Untitled Text"}},"title":"GRADUATE CALENDAR DESCRIPTION"},{"content":{"params":{"text":"
This course is structured as an on-line introductory course for beginning graduate-level researchers for whom a good foundation and preparation in current statistical methods, tools, and applications, particularly in the general area of education, may be required for quantitative research. A variety of teaching and learning approaches will be utilized throughout the course, including recorded and\/or live presentations or lectures, independent reading, mini statistical inquiries, and other on-line learning activities. Multiple assessment practices will be utilized, including on-line concept maps, independent statistical inquiries or experiments, traditional \u201cpen-and-paper\u201d problem sets, a data diary, and two quantitative article analyses.<\/p>\n\n
For the most part, the learning activities in this course have been planned for asynchronous learning where you can plan to work at your own pace and in a flexible manner. That said, you should keep in mind that you should aim to complete each planned Learning Module in the span of a week so that we all might proceed, more or less, at the same pace and complete the course in a timely fashion.<\/p>\n"},"library":"H5P.AdvancedText 1.1","subContentId":"4e821ba0-fca8-40a2-a247-658be1048a61","metadata":{"contentType":"Text","license":"U","title":"Untitled Text"}},"title":"COURSE DESCRIPTION AND INTENTIONS"},{"content":{"params":{"text":"
As a result of planned instruction and active participation, it is reasonable to expect that participants, who successfully complete this course, should be able to:<\/span><\/p>\n\n
\n\tUse descriptive statistical methods to organize, analyze, summarize, and present data in meaningful ways, for example:<\/span>\n\n\t
\n\t\t
Identify, distinguish, and analyze different types of data.<\/span><\/li>\n\t\t
Identify, interpret, and apply computational methods for summarizing and presenting data.<\/span><\/li>\n\t\t
Use appropriate graphical techniques, tables, and summary statistics to highlight key features of data.<\/span><\/li>\n\t<\/ol>\n\t<\/li>\n\t
Use inferential statistical methods to organize, analyze, summarize, and present data in meaningful ways, for example:<\/span>\n\t
\n\t\t
Identify, distinguish, and use different types of inferential statistical tests.<\/span><\/li>\n\t\t
Identify, interpret, and apply computational methods for summarizing and presenting data.<\/span><\/li>\n\t\t
Use appropriate statistical techniques, tables, and summary statistics to highlight key features of data.<\/span><\/li>\n\t<\/ol>\n\t<\/li>\n\t
Identify characteristics of different distributions, e.g., normal and skewed distributions.<\/span><\/li>\n\t
Interpret and construct confidence intervals.<\/span><\/li>\n\t
Describe and illustrate the foundations and process of hypothesis testing, for example:<\/span>\n\t
\n\t\t
Conduct hypothesis testing on sample means.<\/span><\/li>\n\t<\/ol>\n\t<\/li>\n\t
Describe and illustrate correlational analyses between two variables, for example:<\/span>\n\t
\n\t\t
Describe and determine the nature and strength of linear relationships.<\/span><\/li>\n\t\t
Construct scatterplots.<\/span><\/li>\n\t<\/ol>\n\t<\/li>\n\t
Illustrate regression analyses, for example:<\/span>\n\t
\n\t\t
Construct lines of best fit and linear regression equations.<\/span><\/li>\n\t\t
Predict the value of one variable based on the value of the other variable.<\/span><\/li>\n\t<\/ol>\n\t<\/li>\n\t
Describe, interpret, and conduct one-way analyses of variance (ANOVA).<\/span><\/li>\n\t
Read, interpret, and critique relevant educational research publications that employ statistical research techniques.<\/span><\/li>\n<\/ol>\n"},"library":"H5P.AdvancedText 1.1","subContentId":"f38931d3-bb50-43eb-9256-a81537269be7","metadata":{"contentType":"Text","license":"U","title":"Untitled Text"}},"title":"LEARNING OUTCOMES"},{"content":{"params":{"text":"
The course is a fully on-line course, taking place over a period of twelve weeks. You are expected to be prepared to engage in all on-line learning activities, including sharing and discussing with others what you know, have read, and researched prior to planned on-line learning activities.<\/p>\n\n
Prior to the first class, to ensure you have no technical problems logging in, a practice session will be held on:<\/p>\n\n
\n\t
Saturday, January 9, 2021 from 3:00 \u2013 4:00 pm (Eastern Time Zone)<\/strong><\/li>\n<\/ul>\n\n
The first class will be held synchronously, i.e., live and on-line. Specifically, this class will be held on Monday, January 11 from 10:00 \u2013 12:50 pm (Eastern Time Zone)<\/strong>. Please make every effort to be there as it will be important for us to meet for an introduction to the course and to sort out any questions you might have about the class. A recording of the class will be made available for those unable to attend.<\/p>\n\n
Although this course is fully on-line and, for the most part, asynchronous, we still need some kind of structure to follow to ensure we are coordinated and complete the course together at the end. Every week, you will be expected to do some reading\u2014from the assigned text\u2014as noted in the Tentative Schedule, shown in a latter section of this syllabus. You will need to do your required reading prior to starting the planned learning activities in any given learning module. Learning activities, noted later in this syllabus, are described in more detail in the Notes and<\/strong> Guidelines for Assessment Tasks, in the course menu, and are reviewed in each learning module.<\/p>\n"},"library":"H5P.AdvancedText 1.1","subContentId":"972fd6ac-48e9-4313-ba99-1e55dd6cd53d","metadata":{"contentType":"Text","license":"U","title":"Untitled Text"}},"title":"COURSE FORMAT"},{"content":{"params":{"text":"
You will need to acquire only one textbook, which you may purchase from any source, e.g., www.amazon.ca<\/a>, www.chapters.ca<\/a>. Although there are not many differences between different editions, you ought to acquire the 4th Edition, as noted here:<\/p>\n\n
Required Text: Caldwell, S. (2013). Statistics Unplugged. (4th ed.) Wadsworth: Belmont, CA.<\/p>\n\n
You are welcome to acquire an electronic version of this text in the event that you think you might not be able to acquire this text in time to begin this course. Although you can buy different versions, the ebook is sufficient and can be acquired through https:\/\/www.nelsonbrain.com\/shop<\/a><\/p>\n\n
This course website is your central \u201clearning hub\u201d where you also will find a number of supplemental learning materials. These materials are available through the Leddy Library Online Course Resource List System (\u201cLeganto\u201d), which can accessed by clicking the Supplemental Course Readings and Other Suggested Resources link in the course menu. From time to time, additional articles and videos may be uploaded and shared as supplemental materials on the course website in response to the emergent activities of the class and student interests. As you will see, other texts have already been added to the course resource list to enhance your learning on a number of relevant topics. Furthermore, you are also welcome to suggested other texts, articles, and web materials for the class and have them posted to the course website.<\/p>\n"},"library":"H5P.AdvancedText 1.1","subContentId":"afa24332-436f-40ee-ab1d-fe4a0da8c047","metadata":{"contentType":"Text","license":"U","title":"Untitled Text"}},"title":"REQUIRED COURSE MATERIALS AND OTHER RESOURCES"},{"content":{"params":{"text":"
You ought to take some time to review and check your own technical equipment before beginning this course.<\/p>\n\n
First, you will want to ensure that your computer, whether a PC or a Mac, has the most up-to-date Operating System (OS). For this course, there are no special requirements for processor speed, computer memory, or hard drive space. A high-speed broadband (LAN, cable, or DSL) connection is highly recommended, although a wireless connection generally will do just fine. The key, here, is to have a reliable computer with reliable internet connection. Further, you must be comfortable using your own equipment, web browser, installed applications, and the BlackBoard system.<\/p>\n\n
Although you may be familiar with a number of different browsers, e.g. Internet Explorer, Safari, Firefox, and Chrome, some of these browsers are not compatible with Blackboard Collaborate. As you will see, the online BlackBoard tutorial recommends using Chrome as being the best browser to use.<\/p>\n\n
You should also have access to a set of speakers, a webcam, and a set of headphones with a microphone attached. You also will certainly require access to a word processing platform, e.g., MSWord, and, where it might prove useful to you, a spreadsheet application, e.g., Excel.<\/p>\n\n
Finally, it is possible for you to access and interact with most course elements\u2014readings, multimedia, email and discussions\u2014through tablets and smartphones. Although tablets, smartphones, and other mobile devices may allow you to complete some coursework, such devices are not guaranteed to work all the time. As such, you are urged to use a PC- or Mac-based desktop computer or laptop to complete coursework.<\/p>\n"},"library":"H5P.AdvancedText 1.1","subContentId":"b4e06098-e52b-4efa-8693-17c69a9f9409","metadata":{"contentType":"Text","license":"U","title":"Untitled Text"}},"title":"TECHNICAL REQUIREMENTS"},{"content":{"params":{"text":"
For many, if not most, graduate-level courses, one can usually count on spending approximately 10\u201312 hours each week to learn the material and complete that week\u2019s learning and assessment tasks, although the actual amount of time may vary depending on one\u2019s approach to learning.<\/p>\n\n
Yes, this is an on-line course, but the important thing, here, is that what you learn on-line should be no different than if we were meeting face-to-face even though the process of learning will likely be different. All the same, regardless of mode of instruction, the Learning Outcomes are the same.<\/p>\n\n
This doesn\u2019t change the fact that I believe it is important to create an open, inclusive, and challenging learning environment for all. I also expect that you will participate and interact with each other, treating each other respectfully and professionally at all times. This means being prepared for, and ready to participate in, your on-line learning activities, where appropriate or otherwise required. It also means that you engage deeply in your own learning and help others, where and when you are able, in their learning throughout this process.<\/p>\n\n
You can expect to have different opportunities to interact with your course instructor over the term. And, although direct contact with your classmates will likely be minimal, there will be times where you will be able to interact with them in the Discussion Boards and, possibly, elsewhere. You are likely to find other ways to engage in discussions and various on-line activities with some classmates, offering you other occasions to learn from and with one another; you will also find short recorded instructional lectures and reviews, group discussions, other on-line learning activities, and analyses of research articles. You are welcome to use the course website tools to engage with others, if you wish and are able to do so. I am also available to meet with you privately during office hours or as required by requesting some time to talk via the Get Appointment to Meet Dr. Stanley Online<\/strong> link.<\/p>\n"},"library":"H5P.AdvancedText 1.1","subContentId":"fe429afb-a172-4e01-90ed-4a5883ae642d","metadata":{"contentType":"Text","license":"U","title":"Untitled Text"}},"title":"ESTIMATED LEARNING HOURS AND LEARNING EXPERIENCES"},{"content":{"params":{"text":"
This course is an active, on-line learning community. Not only are you expected to be an independent learner, but it is hoped that you also will be able to contribute to the learning of others. In other words, unlike those courses where you may have had an Instructor lecture at you for 3-hours each week, the notion of teaching will be disrupted, here, and should be understood as a shared responsibility. As your Instructor, I will be one of the many people helping you in your learning throughout this course.<\/p>\n\n
As for my part, each week, I have planned activities that may include watching videos and exploring other websites, reading parts of the recommended text and other materials (whether provided or on your own), discussing challenging topics in discussion forums or in small groups, and joining in live discussions in our virtual classroom.<\/p>\n\n
Last, at the start of each week (Sunday), I will be releasing the appropriate Learning Module that you should be engaging in that week and what you should be working on. Naturally, the course website will provide you with additional details as we move through the course and should be the first place you consult if you have a question. I have placed detailed information about assessment requirements on the course website to help you complete those tasks, which should be submitted through the course website or as otherwise indicated. I will also be returning your marked assessment tasks via the course website (Your Assessment Task Grades<\/strong>) and posting your assessed assignments, privately, for your review.<\/p>\n"},"library":"H5P.AdvancedText 1.1","subContentId":"64838721-1424-4014-8f10-0f31ca0eb606","metadata":{"contentType":"Text","license":"U","title":"Untitled Text"}},"title":"WHAT WILL I, YOUR INSTRUCTOR, BE DOING TO HELP YOU LEARN?"},{"content":{"params":{"text":"
Generally speaking, assessment and assessment tasks serve to assist us both in your own learning and to link the learning outcomes with the learning activities. Participation, although generally expected, will not count as part of your final grade\u2014in fact, you should review the Learning Outcomes for what you will be expected to demonstrate. Unlike many other graduate courses in the Faculty, there will NOT be a mid-term examination for this course. The course will be rounded out with two different assignments where you will analyze an appropriate research article as a way to help you develop and enhance your statistical literacy.<\/p>\n\n
The following learning assessment tasks will be elaborated upon in a set of dedicated assessment handouts that may be found on the course website through the Notes and Guidelines for Assessment Tasks link and due dates are noted in the Tentative Schedule Outline<\/strong>.<\/p>\n\n
NOTE<\/strong>: You may upload any assignment, as noted in the appropriate Learning Module, at any time but BEFORE the next Learning Module is released. Assignments uploaded after the next Learning Module is released will be marked late.<\/p>\n\n
\n\t
Weekly Concept Mapping Exercises (20%)<\/li>\n\t
Weekly Statistical Inquiries (20%)<\/li>\n\t
Weekly Problem Sets (20%)<\/li>\n\t
Data Diary: Part 1 (10%)<\/li>\n\t
Data Diary: Part 2 (15%)<\/li>\n\t
Statistics in Quantitative Research: Annotating a Research Article (5%)<\/li>\n\t
Statistics in Quantitative Research: Analyzing a Research Article (10%)<\/li>\n<\/ol>\n"},"library":"H5P.AdvancedText 1.1","subContentId":"af50887a-37e5-4117-9f42-f1aea834cd3f","metadata":{"contentType":"Text","license":"U","title":"Untitled Text"}},"title":"ASSESSMENT AND EVALUATION OF GRADUATE STUDENT COURSE WORK"},{"content":{"params":{"text":"
It is important to be as clear as possible about our expectations of, and responsibilities to, each other. Knowing so in advance helps to ensure that your own learning and experiences are not negatively impacted. Some of these may seem obvious to you, but they still are worth mentioning. We are all members of this on-line class, although you and I have somewhat different roles, but these expectations and responsibilities apply to all of us as members of the same class who have come here to learn.<\/p>\n\nAttendance\n\n
For a fully on-line course, attendance might seem like an odd topic to address. But, we will have at least one scheduled synchronous on-line meeting; please make every effort to show up to these particular sessions on time. This will mean being at your computer, laptop, or device prior to the sessions and logging on in advance to ensure you have no issues. Of course, if anyone logs on late, the class is interrupted and sends a message of disrespect, although technological issues might affect your ability to log into your sessions. Whether for a scheduled whole group session or a planned small group learning activity, if you know or feel you are going to be late, please be courteous enough to let your instructor or group members know in advance with an e-mail. And, similarly, if I will not be available for some reason, I will endeavour to inform the class as soon as possible by posting a notice on the course website and\/or email.<\/p>\n\nPreparing for On-Line Learning Activities\n\n
For the most part, being prepared for your on-line learning activities means having completed readings for the week in question. It is hard to have an informed, productive, intelligent conversation or learning activity if people don\u2019t do their readings. It should be understood that everyone\u2019s participation is required to learn with, from, and about each other. As you prepare for these on-line learning activities, you may find that you have questions: check in with your group mates or feel free to post your questions or comments on-line. And, further, feel free to post any other materials in the threaded discussion fora if you think members of the class would benefit from having access to them.<\/p>\n\nHow to Treat Others\n\n
It is reasonable to expect that there will be some degree of difference in what people believe and sometimes beliefs should be challenged and critiqued, although not in a disrespectful manner. When people do not feel respected or encouraged to contribute, feelings of disrespect, silencing, and fear of ridicule may arise. As such, it is useful to think about how one might experience being in another person\u2019s position when disagreement or questioning arise. Understanding another\u2019s point of view and why she or he might believe such a thing has this way of helping us to see, appreciate, and encourage different points of view. All of this works well when we engage in active listening and ask questions when something becomes unclear. This, of course, requires that we pay attention to each other; otherwise, we can miss out. And, of course, in the world of on-line learning, treating others well is all the more important, especially where so many of the usual communication cues are diminished or otherwise absent.<\/p>\n\nCommitment to Learning and Improvement\n\n
Not only should you be committed to your own learning, but so am I. Feedback is important for all as a means to doing better. As such, you should share constructive feedback with your instructor about the course and the instruction whenever you feel the need to do so, although you will be asked to offer constructive feedback about your experiences throughout the course in different ways. Sharing your concerns allows us to make any reasonable changes or address any problems that may have arisen. As for your own commitment to your own learning, you must also be responsible for your own learning and ensuring that you are not preventing others from learning. Of course, I am here to help you learn, although this is probably a quality everyone should endeavour to carry out. Finally, as is expected here at the University of Windsor, the University\u2019s Student Evaluation of Teaching (SET) survey will be done on-line during the last two weeks of the course, providing me with any important feedback to help make improvements for next time the course may be offered.<\/p>\n\nAcademic Conduct\n\n
It is the policy of the university that instructors mark only original assignments, i.e., not copies. You are encouraged to keep a copy of each piece of work submitted just in case an assignment goes astray.<\/p>\n\nDue Dates\n\n
Assignments should be uploaded, when required, through the provided link in the Learning Module prior to the release of the next Learning Module, as noted in the Tentative Course Schedule. When unexpected circumstances arise, as they sometimes do, please speak with the instructor regarding an extension prior to the due date. Assignments upload after the release of the next Learning Module will be marked Late.<\/p>\n\nStudents Requiring Accommodations\n\n
It is the university\u2019s policy to support students who have identified learning needs, and there are many support services available to students with academic needs at the University of Windsor. Students with special needs who require reasonable accommodations are encouraged to contact the Student Accessibility Services Office (sas@uwindsor.ca<\/a>) early to complete all necessary forms.<\/p>\n\nPlagarism\n\n
Plagiarism is defined as: \"The act of appropriating the literary composition of another, or parts of passages of his or her writing, or the ideas or language of the same, and passing them off as the products of one's own mind.\" (Black's Law Dictionary)<\/p>\n\n
It is expected that all students will be evaluated and graded on their individual merit, where all work submitted for evaluation is the student's own. Of course, students often use or draw upon the ideas of others as expressed in written or published work in preparing essays, papers, reports, theses, and publications. It is imperative that both the data and ideas obtained from all published or unpublished material be properly acknowledged and their sources disclosed. Failure to follow this practice constitutes plagiarism and is considered to be a serious offense. Thus, anyone who knowingly or recklessly uses the work of another person and creates an impression that it is his or her own has committed an act of plagiarism. Plagiarism also includes submitting one's own essay, paper, or thesis on more than one occasion. Accordingly, it is expected that a thesis, essay, paper or a report has not been and is not concurrently being submitted for credit for any other course. A confirmed incident of plagiarism will result in a sanction ranging from a verbal warning, a loss of credit in the course, to expulsion.<\/p>\n"},"library":"H5P.AdvancedText 1.1","subContentId":"b2bb83b9-7462-4f14-9af8-8ff0f52bc8a7","metadata":{"contentType":"Text","license":"U","title":"Untitled Text"}},"title":"EXPECTATIONS AND RESPONSIBILITIES"},{"content":{"params":{"text":"
Each week, Learning Modules are released on Sunday (Eastern Time Zone). Each set of learning activities planned for each Learning Module should be completed before the next Learning Module is released. Directions for uploading any assignments will be provided in the corresponding Learning Module.<\/p>\n\n
A special synchronous online session will be held on Saturday, January 9, 2021, from 3:00 - 4:00 pm (Eastern Time Zone) in Our Virtual Classroom. This session has been created so enrolled students may have a preliminary opportunity to test technology requirements.<\/p>\n\n
There is one planned synchronous session that will be held on January 11 from 10:00 - 12:50 pm (Eastern Time Zone). All other noted times are for office hours and individual tutoring.<\/p>\n\n\n\t\n\t\t\n\t\t\t\n\t\t\t
LEARNING MODULE<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
RELEASE
\n\t\t\tDATE<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
SCHEDULED ONLINE SESSIONS<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
READINGS AND PLANNED ACTIVITIES<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
ASSESSMENT TASKS DUE<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
LEARNING
\n\t\t\tOUTCOMES<\/p>\n\t\t\t\n\t\t\n\t\t\n\t\t\t\n\t\t\t
1<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
Jan. 10<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
ONLINE SYNCHRONOUS SESSION JAN 11 (10:00 am \u2013 12:50 pm Eastern Time Zone)<\/p>\n\n\t\t\t
<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
Introduction and overview of course<\/p>\n\n\t\t\t
Setting the Stage to Show and Assess What We Know: Concept Mapping<\/p>\n\n\t\t\t
A Sample Statistical Experiment<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
<\/p>\n\t\t\t\n\t\t\n\t\t\n\t\t\t\n\t\t\t
2<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
Jan. 17<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
ONLINE OFFICE HOURS AND INDIVIDUAL TUTORING SESSION JAN 18 (10:00 am \u2013 11:00 am Eastern Time Zone)<\/p>\n\n\t\t\t
<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
Chapter 1: The What and How of Statistics<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
Learning Module 2 Concept Map and Discussion Post<\/p>\n\n\t\t\t
Learning Module 2 Statistical Inquiry<\/p>\n\n\t\t\t
Learning Module 2 Problem Set<\/p>\n\n\t\t\t
Ongoing reflections upon your learning for Data Diary: Part 1<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
#1, 9<\/p>\n\t\t\t\n\t\t\n\t\t\n\t\t\t\n\t\t\t
3<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
Jan. 24<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
ONLINE OFFICE HOURS AND INDIVIDUAL TUTORING SESSION JAN 25 (10:00 am \u2013 11:00 am Eastern Time Zone)<\/p>\n\n\t\t\t
<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
Chapter 2: Describing Data and Distributions<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
Learning Module 3 Concept Map and Discussion Post<\/p>\n\n\t\t\t
Learning Module 3 Statistical Inquiry<\/p>\n\n\t\t\t
Learning Module 3 Problem Set<\/p>\n\n\t\t\t
Ongoing reflections upon your learning for Data Diary: Part 1<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
#1, 9<\/p>\n\t\t\t\n\t\t\n\t\t\n\t\t\t\n\t\t\t
4<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
Jan. 31<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
ONLINE OFFICE HOURS AND INDIVIDUAL TUTORING SESSION FEB 1 (10:00 am \u2013 11:00 am Eastern Time Zone)<\/p>\n\n\t\t\t
<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
Chapter 3: The Shape of Distributions<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
Learning Module 4 Concept Map and Discussion Post<\/p>\n\n\t\t\t
Learning Module 4 Statistical Inquiry<\/p>\n\n\t\t\t
Learning Module 4 Problem Set<\/p>\n\n\t\t\t
Ongoing reflections upon your learning for Data Diary: Part 1<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
#1, 3, 9<\/p>\n\t\t\t\n\t\t\n\t\t\n\t\t\t\n\t\t\t
5<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
Feb. 7<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
ONLINE OFFICE HOURS AND INDIVIDUAL TUTORING SESSION FEB 8 (10:00 am \u2013 11:00 am Eastern Time Zone)<\/p>\n\n\t\t\t
<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
Chapter 4: The Normal Curve<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
Learning Module 5 Concept Map and Discussion Post<\/p>\n\n\t\t\t
Learning Module 5 Statistical Inquiry<\/p>\n\n\t\t\t
Learning Module 5 Problem Set<\/p>\n\n\t\t\t
Ongoing reflections upon your learning for Data Diary: Part 1<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
#1, 3, 9<\/p>\n\t\t\t\n\t\t\n\t\t\n\t\t\t \n\t\t\t\n\t\t\t
Feb. 14<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
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READING WEEK<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
NO ASSIGNMENTS ARE DUE<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
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Data Diary: Part 1<\/p>\n\n\t\t\t
Statistics in Quantitative Research: Annotating a Research Article<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
#1, 2, 3, 9<\/p>\n\t\t\t\n\t\t\n\t\t\n\t\t\t\n\t\t\t
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ONLINE OFFICE HOURS AND INDIVIDUAL TUTORING SESSION MAR 1 (10:00 am \u2013 11:00 am Eastern Time Zone)<\/p>\n\n\t\t\t
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Chapter 5: Four Fundamental Concepts<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
Learning Module 7 Concept Map and Discussion Post<\/p>\n\n\t\t\t
Learning Module 7 Statistical Inquiry<\/p>\n\n\t\t\t
Learning Module 7 Problem Set<\/p>\n\n\t\t\t
Ongoing reflections upon your learning for Data Diary: Part 2<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
#1, 2, 3, 9<\/p>\n\t\t\t\n\t\t\n\t\t\n\t\t\t\n\t\t\t
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ONLINE OFFICE HOURS AND INDIVIDUAL TUTORING SESSION MAR 8 (10:00 am \u2013 11:00 am Eastern Time Zone)<\/p>\n\n\t\t\t
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Chapter 6: Confidence Intervals<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
Learning Module 8 Concept Map and Discussion Post<\/p>\n\n\t\t\t
Learning Module 8 Statistical Inquiry<\/p>\n\n\t\t\t
Learning Module 8 Problem Set<\/p>\n\n\t\t\t
Ongoing reflections upon your learning for Data Diary: Part 2<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
#1, 2, 3, 4, 9<\/p>\n\t\t\t\n\t\t\n\t\t\n\t\t\t\n\t\t\t
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ONLINE OFFICE HOURS AND INDIVIDUAL TUTORING SESSION MAR 15 (10:00 am \u2013 11:00 am Eastern Time Zone)<\/p>\n\n\t\t\t
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Chapter 7: Hypothesis Testing with a Single Sample Mean<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
Learning Module 9 Concept Map and Discussion Post<\/p>\n\n\t\t\t
Learning Module 9 Statistical Inquiry<\/p>\n\n\t\t\t
Learning Module 9 Problem Set<\/p>\n\n\t\t\t
Ongoing reflections upon your learning for Data Diary: Part 2<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
#1, 2, 5, 9<\/p>\n\t\t\t\n\t\t\n\t\t\n\t\t\t\n\t\t\t
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ONLINE OFFICE HOURS AND INDIVIDUAL TUTORING SESSION MAR 22 (10:00 am \u2013 11:00 am Eastern Time Zone)<\/p>\n\n\t\t\t
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Chapter 8: Hypothesis Testing with Two Samples<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
Learning Module 10 Concept Map and Discussion Post<\/p>\n\n\t\t\t
Learning Module 10 Statistical Inquiry<\/p>\n\n\t\t\t
Learning Module 10 Problem Set<\/p>\n\n\t\t\t
Ongoing reflections upon your learning for Data Diary: Part 2<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
#1, 2, 5, 9<\/p>\n\t\t\t\n\t\t\n\t\t\n\t\t\t\n\t\t\t
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Mar. 28<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
ONLINE OFFICE HOURS AND INDIVIDUAL TUTORING SESSION MAR 29 (10:00 am \u2013 11:00 am Eastern Time Zone)<\/p>\n\n\t\t\t
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Chapter 10: Analysis of Variance<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
Learning Module 11 Concept Map and Discussion Post<\/p>\n\n\t\t\t
Learning Module 11 Statistical Inquiry<\/p>\n\n\t\t\t
Learning Module 11 Problem Set<\/p>\n\n\t\t\t
Ongoing reflections upon your learning for Data Diary: Part 2<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
#1, 2, 5, 8, 9<\/p>\n\t\t\t\n\t\t\n\t\t\n\t\t\t\n\t\t\t
12<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
Apr. 4<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
ONLINE OFFICE HOURS AND INDIVIDUAL TUTORING SESSION APR 5 (10:00 am \u2013 11:00 am Eastern Time Zone)<\/p>\n\n\t\t\t
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Chapter 12: Correlation and Regression<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
Data Diary: Part 2<\/p>\n\n\t\t\t
Learning Module 12 Concept Map and Discussion Post<\/p>\n\n\t\t\t
Statistics in Quantitative Research: Analyzing a Research Article<\/p>\n\t\t\t\n\t\t\t\n\t\t\t
#1, 2, 5, 6, 7, 9<\/p>\n\t\t\t\n\t\t\n\t\n\n\n
<\/p>\n"},"library":"H5P.AdvancedText 1.1","subContentId":"f8a96d4e-7007-44ca-907c-65fec4d22fc8","metadata":{"contentType":"Text","license":"U","title":"Untitled Text"}},"title":"TENTATIVE COURSE SCHEDULE"}],"hTag":"h2"}

EDUC 8100 W2021 Course Outline

Darren Stanley