PPT and Paper

Course Syllabus

Each student is responsible for his or her access to the internet for purposes of this course and for research. Internet access is a required component of this course and will not be accepted as an excuse for missed work. If you know that you will be traveling, then make sure you plan accordingly.

Note regarding e-mail/voicemail: If you e-mail, please include your name and class title. Please allow up to 48 hours for an email reply. If you leave a voicemail, please remember to include your name, class title, and phone number.

Course Prerequisites

None

Course Description

Use the one from the official description in the Course Catalog. Include any course pre- or co-requisite or other requirement to enroll in the course.

Course Materials

Required Text(s)

A. Bluman, Elementary Statistics 10th Edition, McGraw Hill ISBN 978-125-9755-33-00

R. Kabacoff, R in Action 2nd Edition, Manning Publisher ISBN. 978-161-7291-38-9

Required Software:

R-Studio

R

Program Student Learning Outcomes (SLOs)

CO1: Identify and apply basic probability concepts

CO2: Identify basic statistics measures of central tendency and variance

CO3: Utilize the “R” as a tool set for processing and analyzing basic data

CO4: Demonstrate how the analysis of data impacts operational and strategic decisions

CO5: Visualize data in a compelling way to enable data driven storytelling.

Specialized Knowledge	Broad and Integrative Knowledge	Applied and Collaborative Learning	Civic and Global Learning	Experiential Learning
SLO 1	SLO 2	SLO 3	SLO 4	SLO 5
Integrate the major theories, tools, and approaches in data analytics to identify and successfully communicate data-driven insights for informed decision-making.	Articulate and effectively defend the significance and implications of the work in data analytics in terms of challenges and trends in a local, national or global context.	Apply the principles, tools and methods of analytics to a comprehensive real-world problem or project related to data analyses for tactical and/or strategic decision making; present data, information and/or analytical insights and recommendation s for successful implementation of the project.	Propose an effective path to resolution of an analytical problem that may be complicated by the competitive environment, opposing interests, divergent or uncertain data and information.	Apply the principles, tools and methods of analytics to a project within a sponsoring organization to successfully assist with the extraction, development, delivery, and/or translation/ implementation of data analysis for tactical and/or strategic decision-making in organizations.

.

Course Outcomes

Student learning outcomes are statements indicating the measurable outcomes of the course from the learner’s perspective. They describe the intended purpose of learning: the end results of the learning experience at the course level which should be aligned with the program competencies, program level outcomes, and program map recorded in the College AQA process. These statements answer the question “What should the students be able to do by the end of the course?”

Based on satisfactory completion of this course, a student should be able to:

CO1: Identify and apply basic probability concepts

CO2: Identify basic statistics measures of central tendency and variance

CO3: Utilize the “R” as a tool set for processing and analyzing basic data

CO4: Demonstrate how the analysis of data impacts operational and strategic decisions

CO5: Visualize data in a compelling way to enable data driven storytelling.

Expectations

· Workload

· One (1) academic credit requires 50 minutes a week of classroom or faculty instruction and about two hours of out of class student work for a 15-week course; 100 minutes a week of classroom or direct faculty instruction and about 3.5 hours of out of class student work for a 7.5-week course.

· For a three-credit course, students should expect 2.5 hours a week of classroom or faculty instruction and a minimum of 5 hours of out of class student work for a 15-week course; 5 hours of classroom or direct faculty instruction and a minimum of 10 hours of out of class student work for a 7.5-week course.

· APA citations

Attendance Policy

NA

Course Methodology

Each week, you will be expected to:

1. Review the week's learning objectives.

2. Complete all assigned readings.

3. Complete all lecture materials for the week.

4. Participate in the class discussions and in Discussion Board.

5. Complete and submit all assignments by the due dates.