Sheridan Course Outlines

BUSM70011
Statistics

Land Acknowledgement

Sheridan College resides on land that has been, and still is, the traditional territory of several Indigenous nations, including the Anishinaabe, the Haudenosaunee Confederacy, the Wendat, and the Mississaugas of the Credit First Nation. We recognize this territory is covered by the Dish with One Spoon treaty and the Two Row Wampum treaty, which emphasize the importance of joint stewardship, peace, and respectful relationships.

As an institution of higher learning Sheridan embraces the critical role that education must play in facilitating real transformational change. We continue our collective efforts to recognize Canada's colonial history and to take steps to meaningful Truth and Reconciliation.

Section I: Administrative Information

Total hours: 56.0
Credit Value: 4.0
Credit Value Notes: N/A
Effective: Winter 2020
Prerequisites: N/A
Corequisites: N/A
Equivalents: N/A
Pre/Co/Equiv Notes: N/A

Program(s): Marketing & Sales Certificate
Program Coordinator(s): N/A
Course Leader or Contact: N/A
Version: 20200106_01
Status: Approved (APPR)

Section I Notes: This is a Mohawk College course that is offered through Sheridan CAPS. Students who register for the course through Sheridan will receive credit from Sheridan College only. Access to the course materials will be through OntarioLearn.com.

Section II: Course Details

Detailed Description
This is an introductory course in statistics. This course discusses the following topics: Introduction to Statistics; Introduction to Minitab; Visual Description of Univariate Data: Statistical Description of Univariate Data; Visual Description of Bivariate Data; Statistical Description of Bivariate Data: Regression and Correlation; Probability Basic Concepts; Discrete Probability Distributions; Continuous Probability Distributions; Sampling Distributions; Confidence Intervals and Hypothesis Testing for one mean and one proportion, Chi-Square Analysis, Regression Analysis, and Statistical process Control. Students can use statistics packages Minitab or StatCrunch.

Program Context

Marketing & Sales Certificate	Program Coordinator(s): N/A
n/a

Course Critical Performance and Learning Outcomes

	Critical Performance:
	N/A

Learning Outcomes:

To achieve the critical performance, students will have demonstrated the ability to:

Create a report which summarizes numerical data in a form from which business decisions can be made.
Estimate future or current values for a variable based on current data, using both manual calculations and computer software.
Incorporate the use of probability and risk into decision making.
Integrate probabilities into estimating population parameters based on sample statistics.
Use statistical techniques for estimating population means and proportions.
Use statistical techniques to determine if a current process or belief is true based on sample data.
Use statistical process control techniques to determine if a process is running within acceptable industrial standards.
Use statistical techniques to test categorical and/or multiple independent distributions.
Determine if linear regression is a robust model for predicting a value.

Evaluation Plan
Students demonstrate their learning in the following ways:

Evaluation Plan: ONLINE

	Dropbox	10.0%
	Lab Activity(ies)	40.0%
	Midterm Exam(s)	15.0%
	Final Exam	35.0%
	Total	100.0%

Evaluation Notes and Academic Missed Work Procedure:

TEST AND ASSIGNMENT PROTOCOL

The following protocol applies to every course offered by Continuing and Professional Studies.

1. Students are responsible for staying abreast of test dates and times, as well as due dates and any special instructions for submitting assignments and projects as supplied to the class by the instructor.

2. Students must write all tests at the specified date and time. Missed tests, in-class/online activities, assignments and presentations are awarded a mark of zero. The penalty for late submission of written assignments is a loss of 10% per day for up to five business days (excluding Sundays and statutory holidays), after which, a grade of zero is assigned. Business days include any day that the college is open for business, whether the student has scheduled classes that day or not.  An extension or make-up opportunity may be approved by the instructor at his or her discretion.

Provincial Context
The course meets the following Ministry of Colleges and Universities requirements:

Essential Employability Skills
Essential Employability Skills emphasized in the course:

Information Management - Locate, select, organize and document information using appropriate technology and information systems.
Information Management Skills - Analyze, evaluate, and apply relevant information from a variety of sources.

Prior Learning Assessment and Recognition
PLAR Contact (if course is PLAR-eligible) - Office of the Registrar
Students may apply to receive credit by demonstrating achievement of the course learning outcomes through previous relevant work/life experience, service, self-study and training on the job. This course is eligible for challenge through the following method(s):

Other
Notes: This course is delivered through OntarioLearn at ontariolearn.com and is hosted by (Mohawk College) MO-MATHMA570.

Section III: Topical Outline

Some details of this outline may change as a result of circumstances such as weather cancellations, College and student activities, and class timetabling.
Instruction Mode: Online
Professor: Multiple Professors
Resource(s):

	Type	Description
Required	Textbook	Stats: Data and Models, Loose-Leaf Edition Plus MyLab Statistics with Pearson eText, Deveaux, Velleman, Bock, Pearson, 5th Edition, ISBN 9780135307991, 2019
Required	Other	Minitab License rental (Students purchase Minitab License rentals online. They will be required to provide a campus email address or other proof of academic status.) To purchase simply go to www.OnTheHub.com/minitab and follow the instructions to "Minitab 17"

Applicable student group(s): Continuing and Professional Studies students
Course Details:

1. Create a report which summarizes numerical data in a form from which business decisions can be made.

Construct pareto chart, pie chart, pictograph, stem and leaf, histogram.
Interpret pareto chart, pie chart, pictograph, stem and leaf, histogram.
Identify shape of curve for univariate data.
Calculate numerical measures of centre and variation.
Identify correct measure of centre based on the shape of the curve for univariate data.
Describe a distribution of data, integrating the knowledge of shape into the choice for the numerical measures.
Describe how graphs and choices of numerical summaries can be used to misrepresent data without lying.
Create a computer generated report which summarizes the numerical characteristics of a data distribution.

2. Estimate future or current values for a variable based on current data, using both manual calculations and computer software.

Identify linear trends in a bivariate data plot.
Calculate a measure of the strength, direction and form of a linear relationship.
Calculate the least squares regression line using calculator and computer software.
Assess the fit of the line based on residual plots.
Interpret the coefficient of determination.
Interpret the slope in a "real world" situation.
Evaluate the usefulness of the linear regression as a model for predicting the variable being estimated.

3. Incorporate the use of probability and risk into decision making.

Simulate common events which incorporate probability in their outcomes.
Discriminate between independent events and mutually exclusive events.
Calculate simple probabilities.
Discriminate between categorical (attribute) data and quantitative data.
Identify binomial and normal distributions.
Calculate binomial and normal probabilities.
Identify common real-world occurrences of both the binomial and normal distributions.
Describe probability distributions based on simulated common events.

4. Integrate probabilities into estimating population parameters based on sample statistics.

Simulate sampling from a normal distribution using computer software.
Differentiate between an experiment which proves causality and a survey which shows only a relationship between variables.
Describe the sampling distribution of the means.
Explain the central limit theorem and its importance in estimating population values in such business tools as statistical process control.
Apply the central limit theorem to solving problems involving a sample mean.
Describe the sampling distribution of the proportion.
Describe the difference between attribute sampling distributions and quantitative sampling distributions.
Calculate probabilities using the sampling distribution of the mean or the proportion.

5. Use statistical techniques for estimating population means and proportions.

Integrate probability concepts and sampling techniques to understand the concept of a confidence interval.
Discriminate between sample statistics and population parameters.
Construct a confidence interval for a population mean using both manual calculations and computer software.
Construct a confidence interval for a population proportion usingboth manual calculations and computer software.
Illustrate current examples of confidence intervals found in newspapers, websites, journals, etc.
Write a complete statement which explains a calculated confidence interval.
Explain the confidence level associated with a confidence interval.
Evaluate a current process based on the confidence interval.

6. Use statistical techniques to determine if a current process or belief is true based on sample data.

Formulate a null and alternative hypothesis.
Explain Type I and Type II errors, and the relationship between them.
Calculate and interpret the p-value for a test.
Conduct hypothesis tests on population means and proportions.
Determine the statistical conclusion for the hypothesis test.
Explain with reference to the variable being measured the results of the hypothesis test.

7. Use statistical process control techniques to determine if a process is running within acceptable industrial standards.

Differentiate between common cause and special cause variation.
Determine where the responsibility for correcting each type of variation should lie within the process
Create X-bar and R charts manually and on computer.
Create X-bar and s charts on the computer.
Determine if a process is in control.
Identify which variation in the control chart is "common cause" and which is "special cause" variation.
Differentiate between measurement variables and attribute variables.
Create p-chart for attribute data.
Determine if the process is in control.
Identify common quality standards such is ISO and QS.

8. Use statistical techniques to test categorical and/or multiple independent distributions.

Explain the meaning of independence for two distributions.
Determine if two nominal scale variables are independent using hypothesis test.
Conduct a full hypothesis test to determine if two or more independent samples have equal proportions.
Write a statement in terms of actual variable measured that explains the results of the test.

9. Determine if linear regression is a robust model for predicting a value.

Determine if the assumptions of least square model are met.
Conduct hypothesis test to determine if the individual parameters in linear model are significant.
Interpret the coefficient of determination in terms of the data.
Conduct a hypothesis test to determine if the model as a whole is a significant predictor.
Construct confidence interval for the slope of the equation.
Construct a confidence interval for the estimate for any value of the dependent variable.
Explain the meaning of the confidence interval for the slope of the equation.
Explain the meaning of the confidence interval for the estimate of a value for the dependent variable.

Sheridan Policies

It is recommended that students read the following policies in relation to course outlines:

Academic Integrity
Copyright
Intellectual Property
Respectful Behaviour
Accessible Learning

All Sheridan policies can be viewed on the Sheridan policy website.

Appropriate use of generative Artificial Intelligence tools: In alignment with Sheridan's Academic Integrity Policy, students should consult with their professors and/or refer to evaluation instructions regarding the appropriate use, or prohibition, of generative Artificial Intelligence (AI) tools for coursework. Turnitin AI detection software may be used by faculty members to screen assignment submissions or exams for unauthorized use of artificial intelligence.

Course Outline Changes: The information contained in this Course Outline including but not limited to faculty and program information and course description is subject to change without notice. Nothing in this Course Outline should be viewed as a representation, offer and/or warranty. Students are responsible for reading the Important Notice and Disclaimer which applies to Programs and Courses.

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