Course Materials

Textbook

The textbooks for this course are not required. However, you are strongly encouraged to obtain them, as the reading will provide in-depth explanation to help you better understand the statistical concepts covered in this course.

Bachman, R., & Paternoster, R. (2017). Statistics for criminology and criminal justice (4th ed.). Thousand Oaks, CA: Sage.

Hanneman, R.A., Kposowa, A.J., & Riddle, M.D. (2012) Basic Statistics for Social Research.  Hoboken, NJ: Jossey-Bass/John Wiley and Sons.  

This book is available for free from the ASU Library as an ebook:http://site.ebrary.com.ezproxy1.lib.asu.edu/lib/asulib/detail.action?docID=10626269

Computer Requirements

{Note to instructor: if you require any additional software or technology in this course, please add those details to this list}

Computer System: Windows or Apple desktop or laptop computer manufactured within the last 5 years. Chromebooks and mobile devices will not provide full access to ASU’s online courses.

Operating System: Windows-based computers should be running the most recent version of Windows. Apple computers must be running a recent version of macOS. For operating systems recently released (the last few months), consider maintaining the next most recent release for a few months until bugs in the OS have been addressed.

Required Software: Microsoft Office 365 (available for all students at ASU); Adobe Acrobat Reader DC (free)

Web Browser: Use a recent version of Firefox or Chrome. Students are also advised to have both browsers installed on their computer. 

Internet Connection: Courses are best viewed with high-speed internet and a reliable internet connection. 

Speakers and a microphone: Built-in, USB plug-in, or wireless Bluetooth. A headset with microphone is recommended for privacy and clarity of audio. 

Webcam: Built-in or USB plug-in

Detailed Requirements by Application:

• Canvas LMS computer requirements

Zoom computer requirements  {delete if not relevant}

• Respondus LockDown Browser computer requirements (if used in course) {delete if not relevant}

Honorlock system requirements (if used in course) {delete if not relevant} 

• Need Help? Students needing help with technical issues can contact a 24/7 live chat service at contact.asu.edu or My ASU Service Center for help.

Assignments and Evaluation Procedures

{Required: Briefly describe below the required reading/media, assignments, exams, special materials or extracurricular activities. Explain that the details of these assignments will be provided in class or in the Canvas course. }

Summary of Assignments

• Assignment

Points

• Introduction Discussion

10 points

• Homeworks (6 @ 10 points each)

60 points

• Application Assignments (4 @ 25 points each)

100 points

Final Project

100 points

TOTAL

• 270 points

Reading and Media Assignments

• {Include a statement about how and why you selected the course materials. Give some indication of how primary and secondary materials are assigned (assigned by instructor, self-selected by student) and used; include relevant information about online platforms (e.g., Canvas), libraries, and software that convey these materials. Briefly describe primary and secondary materials (e.g., texts, videos, podcasts, films, but also screenings, performances, field trips, etc.) and how they are assigned (e.g., assigned by instructor, selected by student, drawn from a bibliography).}

Unless otherwise specifically assigned, reading assignments are taken from the required materials specified above. The reading assignments listed for each class are those readings which a student must complete before the class in order to be prepared for class that week. Not all of the assigned readings will be discussed in class; however, all assigned readings may be covered on quizzes, exams, or other assessments.

• Syllabus Quiz {delete if not relevant}

{Instructors are encouraged to require students to take a syllabus quiz to demonstrate their understanding of the course requirements and policies as set forth in the syllabus. At the discretion of the instructor, this may be pass/fail or it may count for a small percentage (e.g., 2%) of the final grade in the course. Alternatively, a minimum score (e.g., 80%) may be required in order to unlock the other course materials contained in the course site on Canvas, our Learning Management System.}

• Introduction

You are expected to introduce yourself to the class in the first week of the class, including where you are from, where you live, what your profession is, and why you are pursuing a Master’s of Arts degree in Criminology and Criminal Justice. This assignment is worth 10 points.

Lectures, Review Slides, and Videos

You are expected to listen to the lectures, review the slides, and watch the videos each week. Materials you obtain from these sources may be covered on homework assignments or other assessments.

Homework

There are six (6) homework assignments, worth 10 points each. With few exceptions, the homework assignment asks you to conduct various statistical analysis discussed in each module in Microsoft Excel. The content and format of the questions on the homework will prepare you for the final project. 

Weekly homework is due on Sunday at 11:59pm, AZ time. Answers and explanations for the homework questions will be available 1 day after the submission date by 10am (i.e., Monday at 10am). {Modify or add to as needed}

Application Assignments

There are four (4) application assignments during the session. Each assignment is meant to enhance your ability to interpret statistical findings published in peer-reviewed academic articles, thus assessing your ability to apply what you learn to real-life research. Each assignment is worth 25 points, for a total of 100 points. 

For each assignment you will be given a set of questions that correspond to two journal articles. The articles differ for each application assignment and are provided to you in advance. You may access and download the assigned journal articles during the week they are assigned. You are expected to answer each question succinctly (most questions will only take one or two sentences to fully answer). Although you can assemble your responses in the downloaded word document, final responses will need to be uploaded to Canvas. The link to each assignment is located in the module where it is assigned. These application assignments can be found in modules 2, 3, 5, and 6, and are due on Sundays in Weeks 2, 3, 5, and 6. {Modify or add to as needed}

Note: Be sure that you understand how responses are expected to be written when working on the homework and application assignments. For example, most questions will only take one or two sentences to fully answer. Ask the instructor is you are unsure. 

Final Project

Each student must complete a final project, which is a cumulative version of all the homework assignments. Specifically, whereas you are typically asked to conduct one analysis in Microsoft Excel in one homework assignment, such as obtaining measures of central tendency, you are asked to perform all the techniques you have learned in this course in Microsoft Excel using an assigned Excel spreadsheet. In addition, you are also expected to interpret the results, especially results associated with hypothesis testing. This final project will be worth 100 points.

Submitting Assignments

All assignments, unless otherwise announced by the instructor, MUST be submitted via Canvas. Each assignment will have a designated place to submit the assignment. Do not submit an assignment via email. {Modify or add to as needed}

Reference

OpenAI. (2023). ChatGPT (Mar 14 version) [Large language model]. https://chat.openai.com/chat

5.(Optional) Share the link of the GenAI conversation in the reference. The ASU Library Guide provides the guidance:https://libguides.asu.edu/c.php?g=1311696&p=9756477.

Sample Language #2: GenAI tools such as ChatGPT may be used in this course, provided that you cite when and how you use the tool. Examples of citing AI language models are available at the ASU Library (https://libguides.asu.edu/c.php?g=1311696&p=9700102).

Sample Language #3: During this course, we may use GenAI tools. You will be informed as to when, where, and how these tools are permitted to be used, along with guidance for attribution.

Sample Language #4 (use sparingly): GenAI may not be used for course assignments except as explicitly authorized by the instructor. The following actions are prohibited in this course [remove non-relevant items]:

Incorporating any part of a GenAI generated response in an assignment;

Using GenAI to brainstorm, formulate arguments, or template ideas for assignments;

?Using GenAI to summarize or contextualize source materials.

Syllabus Disclaimer

The syllabus is a statement of intent and serves as an implicit agreement between the instructor and the student. Every effort will be made to avoid changing the course schedule but the possibility exists that unforeseen events will make syllabus changes necessary. Please remember to check your ASU email and the course site often.

Warning of Course Content 

At times, we may discuss material that may be disturbing—even traumatizing—to some students. This may include strong language (including swear words); graphic descriptions of or extensive discussions of crimes, victimization (including suicide, homicide, rape and sexual abuse, kidnapping, violent assaults, and drug abuse), or disaster scenarios; and depiction or discussion of discriminatory attitudes or actions. If you have experienced criminal victimization or some other type of trauma in your past, you should feel free to excuse yourself from the classroom during a discussion that causes you to experience distress. You will, however, be responsible for any material you miss or, alternatively, for an alternate assignment if you are unable to engage with the material. If you suffer from some form of post-traumatic stress that may be triggered by discussion of material, you are encouraged to formulate a plan for treatment with the relevant health advisers to work on preventing unexpected reactions to potentially triggering material. ASU student counseling services can be reached Monday through Friday from 8am to 5pm at 602-496-1155 or in the Historic Post Office Building, Suite 208. There is also a 24-hour ASU-dedicated crisis hotline at 480-921-1006. 

Keep in mind that some discomfort is inevitable in classes because the goals of higher education include exposing students to new ideas; having students question beliefs they have taken for granted and grapple with ethical problems they have never considered; and, more generally, expanding their horizons so as to become informed and responsible democratic citizens. You may become frustrated from time to time as you struggle with viewpoints that differ from your own. Even if you have previously experienced some form of trauma or victimization, this course may offer you the benefit of helping to understand behaviors in a manner that allows you to process what may have occurred in your past and move forward in your recovery.

Course Policies

For information regarding course and college policies, please refer to the Course Policies link on the course menu. Students are responsible for reviewing and complying with all ASU policies. In this page, you will find important information related to the following: 

?Academic Integrity

?Accessibility

?Attendance, including accommodations.

?Conduct

?Student Success Resources

Module Learning Objectives     

Module 1: Introduction to Statistics

Determine the role statistical analyses play in criminological and criminal justice research

Identify the difference between a sample and a population

Differentiate between the four levels of measurement

Identify variables of different level of measurements

Distinguish between independent and dependent variables

Recognize the unit of analysis in research studies

Module 2: Displaying Data, Frequency Distributions, Central Tendency

Interpret tables and graphs

Interpret distribution shapes

Interpret different measures of central tendency

Specify the strengths and weaknesses of each measure of central tendency

Module 3: Measures of Dispersion

Identify various measures of dispersion

Specify the pros and cons of each measure of dispersion

Determine which measure of dispersion works with qualitative and quantitative data

Calculate measures of dispersion

Identify the rules of probability

Differentiate between mutually exclusive and independent events

Interpret joint probability and conditional probability

Convert values from a variable distribution to z scores to determine the probability of their occurrence

Calculate a z-score

Interpret probabilities associated with z-scores

Module 4: Probability and the Normal Distribution 

Interpret the definitions of confidence intervals

Interpret results of confidence intervals

Interpret the fundamentals of hypothesis testing

Differentiate between type I and type II error

Write an alternative hypothesis

Interpret results of a hypothesis test for one population mean and proportion

Module 5: Confidence Intervals and Hypothesis Testing for One Population Mean and Proportion

Determine when to conduct a hypothesis test involving two population means and how to interpret the result

Distinguish between pooled variance model and separate variance model

Determine when to conduct a hypothesis test involving three or more population means and how to interpret the result

Module 6: Hypothesis Tests Involving Two Population Means and Hypothesis Tests Involving Three or More Population MeansDetermine when to use a chi-square test

Interpret hypothesis tests with categorical data

Interpret results of hypothesis tests with categorical data

Calculate and interpret the correlation coefficient.

Differentiate between a positive and negative relationship

Interpret results of hypothesis tests involving correlations

Module 7: Hypothesis Testing with Categorical Data and Correlation

Final Project

Pacing, and Content Availability

{State policy on course pacing and content availability}

Sample Language 1: This course is designed to encourage the absorption of content and interaction throughout the session. Though you can review content and read ahead, assignments will not be released until the week they are to be reviewed and discussed. To allow individuals to work ahead goes against the purpose of some course activities like discussions. 

Sample Language 2: This Course Uses “Requirements” and “Prerequisites” to control access to modules. In other words, certain tasks in one module must be completed before students will have access to a subsequent module. Requirements are conditions that must be completed for students to complete a module. Requirements include viewing particular pages in a module, completing assignments, or contributing to discussions, and so on. Prerequisites are conditions that must be completed for students to begin a module. Prerequisite conditions check whether students have completed particular requirements. Some prerequisites may be set to require completion of multiple requirements, thereby making students complete multiple tasks before being able to see new materials. 

Course Structure and Schedule

{Suggestion: Add Course Structure info here.}

Sample Language: This course [meets weekly] [is a fully online course with no required meetings] [is a hybrid course meaning we will meet in person as per the schedule below while the remaining course is online] [is an ASU Sync course meaning we will meet in the designated Zoom room for weekly class meetings].

Here is an outline of the material we may cover.  We may vary from this schedule depending upon the time the professor feels we need to spend on any topic.  Therefore, use this schedule with the caveat that assignments may be changed by the professor for any given class session.

{Modify this schedule to conform to your preferred scheduled format, whether using a weekly format or a module-based format. Delete the weeks/modules you do not need.}

ACTIVITIES/ASSIGNMENTS  

POINTS  

DUE DATE  

Week 1

MODULE 1: Introduction to Statistics

Introduction Discussion  

10

MM/DD

Homework 1  

10  

MM/DD

Week 2

MODULE 2: Displaying Data, Frequency Distribution, and Measures of Central Tendency

Homework 2

10  

MM/DD

Application Assignment 1

25

MM/DD

Week 3

MODULE 3: Measures of Dispersion, Probability and Normal Distribution

Homework 3 

10  

MM/DD

Application Assignment 2

25

MM/DD

Week 4

MODULE 4: Confidence Interval and Hypothesis Testing for One Population Mean and Proportion

Homework 4

10

MM/DD

Week 5

MODULE 5: Hypothesis Testing Involving Two Population Means and Hypothesis Testing Involving Three or More Population Means

Homework 5

10

MM/DD

Application Assignment 3

25

MM/DD

Week 6

MODULE 6: Hypothesis Testing with Categorical Data and Correlations 

Homework 6

10

MM/DD

Application Assignment 4

25

MM/DD

Week 7

Final Project

100

MM/DD

{ASU policy specifically prohibits faculty members from administering final exams (or similar summative assessments) during the final week of classes for all in-person courses.  Thus, all instructional faculty members are required to teach for the 15 weeks of the semester and then administer a final assessment during finals week, which is the 16th and final week of the semester.

By contrast, faculty teaching online are required to administer their final exams (or similar summative assessments) on the last day of an online session. For more information, consult ASU’s official policy on final exams at this link:https://www.asu.edu/aad/manuals/acd/acd304-01.html).}