▶️ icons are links to a video in support of the section
⭕ is a quiz in Canvas
Course pace: The course has new material with homework on the schedule shown in the calendar. You will need to engage with the course on a regular and substantive basis.
Submissions policy: Homework is due by the start of the next class day. Late homework can be submitted for up to a week after the due date. After a week, the homework locks, cannot be submitted, and will have a negative impact on your grade.
Participation policy: The homework occurs in Google Sheets. Google Sheets supports interactive commenting. This will be one of the principal means by which we interact as I provide guidance on how to correct errors made in the homework. Participation will also be tracked via analytics available in Schoology.
Communication policy: I can be contacted through the messaging capability in Schoology or via email at danaleeling@gmail.com. You can also contact me through these channels to request to set up a Schoology conferences or Zoom meeting with me. I do make every effort to respond to messages within 24 hours. Additional contact information: Cell: 921-7961
Calendar structure: The calendar is driven by the logic of where college campuses are closed. When the national campus is closed, the residential section cannot meet, all students in the course get that holiday. Note that the approval of distance education courses was contingent on them being offered under the aegis of the national campus, hence the use of the national campus calendar. Where other state campuses are closed for state holidays , students may have computer or Internet access issues at that campus. For these students the assignment is shifted to by a day forward or backward as appropriate.
Grading policy:
Points are earned for correct answers on homework, tests, and presentations.
You have do consistently well across all material to succeed in this course.
Grading is based on the standard college policy: Obtain 90% of the points or more to
obtain an A, 80% to 89% for a B, and so forth.
Academic integrity policy: This course operates on an honor system: your honor. Your trustworthiness. Unless working on a group assignment, do your own work. Submit only your own work. Do the right thing. Always.
Course student learning outcomes assessment: Data from Canvas
Learning outcomes in brief: Students will be able to... Institutional Learning Outcomes:
4. Problem solving: capacity to design, evaluate, and implement a strategy to answer an open-ended question or achieve a desired goal.
8. Quantitative Reasoning: ability to reason and solve quantitative problems from a wide array of authentic contexts and everyday life situations; comprehends and can create sophisticated arguments supported by quantitative evidence and can clearly communicate those arguments in a variety of formats. Program Learning Outcomes:
3.1 Demonstrate understanding and apply mathematical concepts in problem solving and in day to day activities
3.2 Present and interpret numeric information in graphic forms Course Learning Outcomes:
Perform basic statistical calculations for a single variable up to and including graphical analysis, confidence intervals, hypothesis testing against an expected value, and testing two samples for a difference of means.
1.1 Calculate basic statistical measures for the middle, spread of data including quartiles and relative standing
1.2 Generate box plot and histogram charts from data
1.3 Calculate confidence intervals, perform hypothesis tests against a known value, test two samples for a difference of means, calculate effect size
Perform basic statistical calculations for paired correlated variables.
2.1 Calculate the linear slope, intercept, nature and strength of the relationship for paired data
2.2 Generate scatter graphs for paired data
2.3 Predict values based on the regression function
Engage in data exploration and analysis using appropriate statistical techniques including numeric calculations, graphical approaches, and tests.
3.1 Generate appropriate basic statistical measures of the data without specific guidance on which measures should be calculated
3.2 Generate appropriate charts and graphs for the data without specific guidance on which charts should be generated
3.3 Draw conclusions based on statistical analyses and tests, obtain answers to questions about the data, supported by appropriate statistics
