Course Title: MATH 14S Statistics With Support
Course Section & Term: Section F8773, Fall 2024
Number of Units: 6
Meeting Days & Locations: Wednesdays 3-4:50pm, Redding Main Campus, room 1102
Note: this is a hybrid course. In addition to Wednesday meetings, the majority of the course (learning activities and assignments) will take place via Canvas
Prerequisite: Intermediate Algebra as determined by Multiple Measures or Math Placement Level 4 or higher
This is an introductory course in statistics with a support component that is designed to help the student who needs additional support to be successful. It will show the role of modern statistical methods in the process of decision making. Concepts are introduced by example rather than by rigorous mathematical theory. The following topics will be covered: measures of central tendency and dispersion, regression and correlation, probability, sampling distributions including the normal, t, and CHI-square, and statistical inference using confidence intervals and hypotheses testing.
Students will analyze statistical distributions and relationships of given data using numerical, visual, and technological methods.
Students will draw valid conclusions about population parameters using appropriate hypothesis tests, interval estimation, technology, and written explanations.
Organize statistical data.
Determine the 5-number summary, mean, and standard deviation of a data set.
Compute the probability of an event.
Compute the probability of a compound event consisting of independent, dependent, or mutually exclusive events.
Compute probability of an event using the binomial and normal distributions.
Test hypotheses about sample means and difference of two sample means using the normal distribution and large sample theory.
Test hypotheses about sample means and difference of two sample means using the t distribution and small sample theory.
Calculate confidence intervals for population means and population proportions.
Use CHI-square distribution to test hypotheses concerning contingency tables and "goodness of fit."
Determine the linear regression of a variable upon another variable.
Use linear regression for estimation and inference, and interpret the associated statistics.
Use ANOVA for estimation and inference, and interpret the associated statistics.
Use technology in statistical analysis.
Organization of data
Mean, median, and standard deviation
Probability
Binomial Distributions
Normal Distributions and the Central Limit Theorem
Confidence intervals
Hypotheses testing using large sample theory
Hypotheses testing using small sample theory
Regression and correlation
CHI-square distribution and its use
Analysis of Variance (ANOVA)
This is a 6 unit course which may need up to 14 hours of your time per week. (WOW!) This includes 4 hours of statistics instruction online, 2 hours of instructor support in person, and 8 hours of work on assignments, class activities, and study time.
Outside of class, all other coursework can be completed on Canvas at your convenience during the week. Please plan to actively participate by interacting with instructional materials and assignments! Specifically, these are the participation guidelines I hope you will follow:
check-in and interact in the course at least twice a week;
participate in Canvas discussion boards and learning activities;
submit all assignments;
connect with me beforehand if you're going to be disconnected from the course for a week or more.
You might be thinking "Hmm, who will even notice if I'm online or not?" Thanks to Canvas analytics, I can see lots of information about your participation patterns in the course. Rest assured, I will reach out with a friendly "hello! are you there?" if it seems like you're losing traction. 🙂
If a student misses two consecutive weeks of class or more it may be assumed they are no longer interested in the course. School policy notes that these students may be dropped by the instructor either on census day or via the instructor-initiated drop process. Nevertheless, if the student decides to stop attending, it is always the student’s responsibility to officially drop or withdraw from the class.
Following these school guidelines, this is my approach to attendance:
If you miss 2 or more weeks of class (meaning, you're not active on Canvas or not present on Wednesdays), I will email you to discuss whether you plan to continue the course.
If you plan to drop the course, you should do so through the Shasta Portal or by submitting the appropriate forms.
If you plan to continue the course, I will politely pester you to commit to a schedule for catching up on your missed work.
If I do not hear from you, I will assume you are not interested in the course and will drop you from the roster.
Please see "Dates to Remember" in this course guide for details about drop deadlines.
In the spirit of a learning community, working within the class schedule allows for interaction with classmates and gives you time to incorporate feedback from me. It also helps me plan my time and ensure more objective grading.
I understand you have other commitments outside this class or may need more time to process the course material. If you would benefit from a deadline extension, please email me at abarto@shastacollege.edu or through the Canvas inbox.
In your message, it is helpful if you communicate (1) the name of the assignment and (2) proposed timeframe for completing the work. You do not need to give a reason or share personal details to request more time, though you’re welcome to share anything you think would be helpful for me to know.
Individual learning activities like quizzes, activities, journals, written assignments: flexible. I typically leave quizzes & activities unlocked in Canvas throughout the semester. If they are ungraded practice assignments, you may want to repeat them to prepare for tests and such.
Group discussions: moderately flexible. I want you to benefit from participating, but I'd also like to wrap up these discussions as the class moves on to a new unit.
Tests: a few days as needed. I would like to release answers and debrief with the class within a week.
Final project: no extensions.
I try to send deadline reminders, especially for the first few major assessments, but the responsiblity is on you to keep track of deadlines and "last call!" reminders for late work. The course is designed with some flexibility, so if you forget or can't submit something, just keep going. You can still succeed in the course.
The last day of the semester is the last day I accept coursework. This allows me the necessary time to calculate and submit your final course grades by the college deadline.
If you email me last-minute to request an extension that falls within my syllabus guidelines, please assume it will be granted. For example, if a test is due at midnight and you email me at 11pm, I won't reply that night but will definitely agree to an extension the following day. Please don't take a test that you're not ready for, simply because you're not sure if I'll say yes!
If you are requesting something outside the guidelines, please do not assume. For example, if your test is already a week late and I've done a "last call," I most likely will not give you more time. I will also not grant extensions after the course ends. In these cases it would be best to do whatever you can in the time you have left.
If you are experiencing an emergency or extenuating circumstance, please keep me informed, as you feel comfortable. Did you know that Partners in Access to College Education (PACE) serves students with permanent disabilities and temporary conditions? You may be eligible for accommodations if you are experiencing any of the following:
Temporary conditions: pregnancy, long Covid, broken bones, etc.
Mental health needs
Learning disabilities
Acquired brain injuries
ADHD
Intellectual disabilities
Autism spectrum
Blind/low vision
Deaf/hard of hearing
Physical disabilities
Refer to the PACE webpage for more information about accommodations and support.
All assignments will receive some type of feedback, but not all will receive a grade. Both feedback and grades will be communicated through Canvas. Here are some examples of the types of grades and feedback you will see:
Rubrics - details for how your work was graded, areas of excellence, areas for improvement
Instructor comments - to help you improve
Numerical grades - for example, 8 points on a 10 point assignment
Complete/Incomplete grades - a "✅" checkmark symbol means you have completed the assignment requirements and earned the maximum number of points. An "X" means the assignment is incomplete or missing a few components.
Grades for this course are an attempt to quantify and summarize your learning. This is a messy process at best! I do my best to grade in a way that reflects only your learning and not behaviors or outside circumstances. Some specifics:
No grades for missing assessments, with the exception of the final project. If you haven't submitted work, I can't determine how much you've learned. I will report this as "excused" or "missing" in the gradebook.
No grade penalties for late work. If an extension is granted, you can earn up to full credit for your work. I am grading your assignment, not the circumstances that led to late submission.
No inflated "completion grades" during the semester. This is why some assignments will receive comments rather than numerical grades.
No "bad grades" during the naturally imperfect learning process. You are encouraged to make mistakes while learning: there is neurological evidence that mistakes lead to a stronger brain. This deserves a reward not a penalty! You can expect encouraging, constructive feedback during this phase of your learning.
Holistic review of your grades at the end of the semester, and use of professional judgment to assign a final grade. Primarily, I look at your progress throughout the semester and consider whether you ultimately demonstrated mastery of course concepts & skills. This does not mean you can skip all of the learning assignments and tests and just do the final project! I need to see a pattern of progress and improvement in your work throughout the semester.
Please check out the Canvas Student Guide: All About Grades for info & examples about accessing your grades, instructor comments, and rubric scores on Canvas.
Course assignments are divided into two main types: learning assignments and mastery assessments.
Learning (Practice) Assignments - 0% of your course grade
The purpose of these assignments is to build up your knowledge and skills, so these assignments do not count toward your final grade. Just like practicing a sport or an instrument, they are still very important, and you should complete them in order to be successful! No one wins a basketball tournament without practicing.
Typically these assignments will receive feedback or a complete/incomplete grade, but not a numerical grade. I may at times recommend that you revise or retry these to continue your learning.
Mastery Assessments - 100% of your course grade
The purpose of these assessments is to demonstrate your learning - your mastery of statistics knowledge & skills. This includes tests, the final project, and any "final" check of your learning such as a journal entry or activity.
Grades will either be percentage points (e.g. 85%) or mastery scores based on a rubric/checklist (e.g. "exceptional mastery of outcomes" or "outcomes not yet mastered"). I will provide specific details along with each assessment.
In your Canvas grades, you can check under an assignment title to see whether it's categorized as a learning assignment or a graded assessment.
Unit 1 Statistical Process & Sampling:
Learning Assignments: Discussion, Quiz, Data Collection Survey (feedback but no grade)
Assessments: Journal Entry (5% of course grade)
Unit 2 Descriptive Statistics:
Learning Assignments: Discussion, Quizzes, Activities (feedback but no grade)
Assessments: Tech Assignment, 1 Test (15% of course grade)
Unit 3 Statistical Theory & Random Variables:
Learning Assignments: Discussion, Written Assignment, Quizzes, Activities (feedback but no grade)
Assessments: 1-2 Tests (25% of course grade)
Unit 4 Inferential Statistics:
Learning Assignments: Assignments, Quizzes (feedback but no grade)
Assessments: 1-2 Tests (30% of course grade)
Unit 5 Statistical Results & Analysis:
Learning Assignments: Journal, Discussion (feedback but no grade)
Assessments: Final Project (25% of course grade)
Your overall course grade will be reported as a letter grade that represents your overall mastery of the objectives and student learning outcomes for the course. All graded assessments will accumulate either mastery ratings (for example, assignments graded with a rubric) or percentage points (for example, tests), which translate to a letter grade as follows:
A - Exceptional Mastery of Course Concepts (90-100%)
B - Mastery of Course Concepts (80-89%)
C - Mastery of the Majority of Course Concepts (70-79%)
D - Mastery of Some Course Concepts (60-69%)
F - Course Concepts Not Yet Mastered or No Evidence of Mastery (below 60%)
In lieu of extra credit, I believe the above-described grading methods will help you succeed. I hope you will use any offered opportunities for revisions, correct your work based on feedback, collaborate with others, advocate for yourself, ask questions, and enjoy the learning journey. Let's chat if you are concerned about your grade: we can review your work and customize a plan to get you through the course. 👍
At Shasta College you are part of an academic community. Teachers, students, librarians, professionals, administrators - all of us are here for the common goal of helping you learn. Being part of this community is an exciting opportunity that also comes with responsibilities and expectations. Academic integrity is "the expectation that...all members of the academic community act with: honesty, trust, fairness, respect and responsibility" (TEQSA).
Academic integrity is also defined by what it is not. Here are the behaviors that Shasta College considers academically dishonest:
"Cheating, plagiarism (including plagiarism in a student publication), or engaging in other academic dishonesty. Academic dishonesty is the willful and intentional fraud and deception for the purpose of improving a grade or obtaining course credit, and includes all student behavior by fraudulent and/or deceptive means. The student has the full responsibility for the content and integrity of all academic work submitted."
To read the academic integrity policy and your other ethical responsibilities, view the Current Students area of the college website and select "Academic Honesty" and "Student Code of Conduct" in the navigation menu.
I'm glad you asked! 😄 Academic integrity ensures that...
your work is an accurate reflection of what you've learned.
your instructor can use your work to help you improve.
you haven't stolen someone's intellectual property.
education is equitable: no one has an unfair advantage over someone else.
you can take pride in your work and your degree!
The academic integrity guidelines for this course are very simple.
Please DO...
your own work. If you want to learn, you need to do the work!
use all the resources available to you - information on Canvas, the internet, your textbook, the library.
collaborate with other people in the academic community - classmates, tutors, instructors, college staff.
ask for clarification if you don't understand the difference between copying answers and using resources for reference.
consider other options before you cheat! Did you ask for a deadline extension? Can you reach out to academic staff or a mental health professional before school or personal concerns become too overwhelming?
Please DON'T...
ask someone else to do your work for you.
use resources the instructor asks you not to use. You should not use answer keys or "expert answers" from online while you complete assessments.
collaborate when assignment instructions state that you should work alone. You will work alone to take tests.
copy someone else's work. You may look at answer keys to help you with assignments (not tests), but you should not just copy the answers. If it's not your answer, don't submit it.
get overwhelmed by stress. Many people cheat as a survival tactic when under a lot of pressure. Before you get to that point, send out an SOS! Your instructor, tutors, college staff are a few people you can turn to for support.
Yes! We will incorporate AI in class through some assignments and instruction, and I will give you tips on how to use it as a statistics tutor. My favorite is ChatGPT, though the college is trying to convert me to Copilot. 🙂 This is obviously a quickly-evolving topic, and we are all trying to figure out what this means for ethics and innovation.
My current AI policy is: as best you can, use it with integrity and creativity. I am not able or willing to micromanage how you do this, but I will try to explain my expectations as we go. Some thoughts...realize that AI tools are not always right: sometimes information is incorrect or unethically sourced. Don't use it to generate answers for you, but do use it to enhance your understanding. An AI chatbot can certainly ace this course for you. But are you here to learn or outsource your brain? 🙃 Too much AI use and you risk losing opportunities to grow and become a smarter, more creative human. Too little AI use and you may miss some exciting innovations and tools that can make your life easier.
The college offers workshops and resources if you are interested in becoming a better AI user - ask for details!
💻 The best way to reach me is during my student hours (office hours): I'm available on Zoom or in person - details are on the home page of this course guide.
✉️ Please feel free to email me at abarto@shastacollege.edu or through the Canvas inbox with any private questions or communication.
💬 If you have a question about course concepts or something that would benefit everyone, please post it in the Q&A discussion on Canvas. If you email me privately about this type of question, I'll post an answer in the Q&A discussion and direct you there. (I receive many repeat questions, so this will help me get back to you right away and be consistent with the same answer for everyone!)
I'll communicate with you regularly via Canvas announcements: please read these. 🙂 You can expect extra resources, interesting statistics findings, previews of new unit topics, unit reviews and summaries, general feedback about assessments, reminders and tips, etc.
I will also provide individual feedback on key learning assignments and your major graded assessments. You can access instructor comments and rubric feedback in your Canvas grades. Expect grades & feedback within about a week of the assessment due date. Please feel free to reach out if you are waiting on something from me.
I will read and guide class discussions by responding to main threads of thought, prompting you to dig deeper into a concept, correcting misconceptions, answering lingering questions, and summarizing key takeaways. I'll do this via Canvas announcement (written or video) since not everyone returns to discussions after posting. I may also respond to a few posts within the discussion and mention this in an announcement.
You have options! If you're comfortable reaching out, please feel free to initiate. We likely have many who are eager to chat but reluctant to start the conversation. Here are some ideas:
Post in the "Student Lounge" discussion board in Canvas
"Chat" in Canvas course with others online at the same time.
Use Canvas inbox to message the entire class or a few classmates.
Check "People" in our course navigation menu to find names of everyone in the class.
Set up a study group in person or online.
Group text or video call a few classmates to chat, study, etc.
Find a "study buddy" to email or text throughout the semester.
We have student spaces on all of our campuses (lounges, study rooms) if you want to connect in person. Zoom, Google Meet, or FaceTime could work for online meetups. Let me know if you need help with the details.
Only authorized persons are allowed in the classrooms. College liability coverage does not extend to guests or children and thus they are not allowed in the classroom.
The Shasta-Tehama Trinity Joint Community College District (“Shasta College”) does not discriminate against any person on the basis of race, color, national origin, sex, religious preference, age, disability (physical and mental), pregnancy (including pregnancy, childbirth, and medical conditions related to pregnancy or childbirth), gender identity, sexual orientation, genetics, military or veteran status or any other characteristic protected by applicable law in admission and access to, or treatment in employment, educational programs or activities at any of its campuses. Shasta College also prohibits harassment on any of these bases, including sexual harassment, as well as sexual assault, domestic violence, dating violence, and stalking.
If a student misses two consecutive weeks of class or more it may be assumed they are no longer interested in the course. School policy notes that these students may be dropped by the instructor either on census day or via the instructor initiated drop process. Nevertheless, if the student decides to stop attending, it is always the student’s responsibility to officially drop or withdraw from the class.
According to the Shasta College Student Handbook and the Shasta College Catalog, there are a number of unauthorized behaviors that violate the campus academic honesty policy. Each student should become familiar with the policy.
Failure to acknowledge the work of other scholars constitutes an egregious breach of ethics and is a violation of civil law. You must, in all cases, do your own work, acknowledge sources, and document them appropriately. Otherwise, disciplinary sanctions will be applied. If you have any questions about plagiarism, please do not hesitate to contact me. In other words, cheating of any sort will not be tolerated and will result in an “F” for the assignment, quiz, or exam, and the case may be reported to Student Services, which may result in an “F” for the course.
In accordance with the Student Code of Conduct (Board Policy 5500), students are expected to obey all California State laws and all Federal laws that pertain to behavior on a college campus. Shasta College’s jurisdiction and discipline shall be limited to conduct that occurs on Shasta College premises or that is related to school activities. Any student found to have committed misconduct is subject to the disciplinary sanctions outlined in Board Policy, Section 5520.
Academic adjustments due to a disability or serious medical condition: Students should contact the office of Partners in Access to College Education (PACE) for authorization of academic adjustments (accommodations) for this course. The office is located in room 2006 (242-7790). Students will need to provide documentation that verifies the condition and the type of limitations that may result. The staff in PACE have been designated with the authority to 1) evaluate that documentation, 2) determine which academic adjustments are appropriate to this course, and 3) facilitate the provision of approved academic adjustments. Students will submit notices directly to the course instructor regarding specific academic adjustments that are authorized for this class.
Shasta College has many resources that can help you with both academic and life challenges. Visit The Hub to browse your options or get connected with an advisor. Some specific resources, many with options for remote learners, are listed below.
To help you learn:
To help you thrive: