Please note that the specifics of this Course Syllabus are subject to change. Instructors will notify students of any changes and students will be responsible for abiding by them. Even if you print this syllabus, please check the online version often.

Description

When cyberattacks occur, can we tell if there is a relationship between the number of people affected and the financial loss incurred by an organization?

Does the type of cyberattack used have an impact on the number of records breached?

When terrorist events occur, can we tell if there is a pattern between the year of attacks and the country of origin of the attacker?

This semester, you’ll learn how to test questions like these using statistical analyses. The first week of the semester will involve a brief review of foundational data analysis concepts (see L01 and L02 under Modules). We will then discuss how to analyze data with different levels of measurement and distributions in L03 to L12. These techniques will include simple regression, multiple regression, logistic regression, chi-square analysis, and log-linear analysis. You will primarily be using R to analyze data, which is a free powerful software package that is used extensively in multiple fields and industries.

Prerequisites

• STAT 200

Objectives

At the conclusion of this course, you will be able to:

• Recommend the most appropriate data analytic technique to use based on the level of measurement and distribution of the data
• Conduct a variety of data analytic techniques including, simple regression, multiple regression, logistic regression, chi-square analysis, and log-linear analysis
• Interpret these results for both academics and practitioners
• Describe the limitations and assumptions made about the data for each of these data analytic techniques
• Use packages from R to statistically test relationships between and among variables

Instructor

• TBA
  
  • Instructor information can be found by selecting People and then the Teacher name.

All course-related emails to the instructor should be sent within Canvas, using the Inbox. Every attempt will be made by the instructor to respond to emails within 24 hours. 

Course announcements will be used on a regular basis by the instructor to share important information related to the course. Please be sure to have your notification settings for Announcements set to "Notify me right away". Please click the following link for details on how to do this: Setting Canvas Notifications You are responsible for reviewing all announcements made in the course in a timely manner.

Materials

• No textbook is required

Assignments & Grading

Labs and Exams are the two graded assessments used in this course. Both types of assessments are open-book. However, you will need to complete all of your coursework on your own and your submissions should adhere to Penn State's academic integrity policy.

Labs

• There will be a total of 12 Labs in the course that are worth 20 points each.
• Only your top 11 Lab grades will be used to determine your final grade.
• These assignments are therefore worth a total of 220 points or 55% of your grade.

Exams

• There will be a total of 3 Exams in the course that are worth 60 points each.
• All three exams will be used to determine your final grade.
• These assignments are worth a total of 180 points or 45% of your grade.

All assignments are due 11:59 PM EST by the last day of the week (Sunday) unless otherwise noted and will be graded the same week by Wednesday at 8:00 AM EST. Assignments submitted after the stated deadline (starting at 12:01 AM on Monday) will be assigned a 10% penalty per day late. Late assignments will not be accepted more than 2 days after the original deadline. Late assignments will be graded in the next round of grading and will be released by the following week Wednesday at 8:00 AM EST. 

Course Grading Scale

The following are the minimum cutoffs for each grade:

• 93.00% = A
• 90.00% = A-
• 87.00% = B+
• 83.00% = B
• 80.00% = B-
• 77.00% = C+
• 70.00% = C
• 60.00% = D
• less than 60.00% = F

Final grades are imported directly from Canvas into LionPath at the end of the semester. The grade that you see displayed in Canvas will be the grade that you will see displayed in LionPath. There will be no manipulation of grades after the semester has ended, which includes the rounding of points or percentages. The grading scheme displayed above is integrated into the grading scheme displayed in Canvas and is consistent with the recommended grading system from the College of IST and Penn State. 

Course Policies

Your Responsibilities for this Course

• To Ask Questions
• You are also encouraged to ask the instructor or teaching assistant questions BEFORE submitting a graded assignment if you are unsure about a concept or the wording of a question.
• Any such concerns raised after the submission of a graded assignment are unlikely to be honored.
• To Complete Assignments Early or On-Time
• All assignments are due 11:59 PM EST by the last day of the week (Sunday) unless otherwise noted. Assignments submitted after the stated deadline (starting at 12:01 AM on Monday) will be assigned a 10% penalty per day late. Assignments will not be accepted more than 2 days after the original deadline.
• Given the online nature of this course, you are encouraged to submit your assignments early to avoid late submissions due to technical difficulties. You are also encouraged to submit assignments early if you have a scheduled event or religious holiday that overlaps with a given deadline.
• To Maintain Academic Integrity
• Academic integrity is taken seriously in this course. All assignments should be completed individually. These submissions should be your own original work.
• See additional information on academic integrity in Penn State’s policies below.
• Logging into Canvas
  • Students are expected to log in regularly to check the course announcements, lessons, and emails.
• Emailing through Canvas
  • Students are expected to use Canvas for all course email communication.