⭕ are tests in the Instructure Canvas learning management system
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Course pace: The course has new material with homework every weekday Monday to Thursday with tests usually on Friday. You will need to engage with the course on a daily basis.
Submissions policy: Homework is due at the start of the next class day. Late submissions are accepted up to a week late.
Participation policy: The homework occurs in Google Sheets. Comments on assignments in Canvas will be one of the principal means by which we interact as I provide guidance on how to correct errors made in the homework.
Communication policy: I can be contacted through Inbox capability in Canvas. Cell: 926-2868
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. Submit only your own work. Do the right thing. Always.
Course student learning outcomes assessment:
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
