MAking Sense of Big Data Learning Community
MAT 135Elementary Statistics & CTA 100 Computing & Information Technology
12:00-12:50 MWF & 1:20-2:30, Fall 2016
Professors / Betsy McCall, M.A., M.S.,
Assistant Professor of Mathematics
Adjunct Faculty in Computer Information Systems
Anne Arundel Community College
(410) 777-1264
Mathematics 231J / Michael J. Waters, M.S.
Adjunct Faculty of Computer Technology
Anne Arundel Community College
410-881-4600
CALT
Office Hours / M 1:00-5:00 p.m., T 6:00-7:00 p.m., W 1:00-2:00
In Math 231J in CALT / By appointment
Course Websites / Canvas Course
Online Homework MyLabsPlus
Archive Site betsymccall.infoor / Canvas
Learning Community Description / The CTA 100/MAT 135 Learning Community will focus on how technology is used in the data collection, analysis, and interpretation processes. Students will share assignments as they look at data using topics of the Internet, social media, cybersecurity, and diversity in STEM fields. Students will gain proficiency in application software (word processing, spreadsheet, database and presentation graphics) through analyzing and interpreting data sets. At least 50% of the content of both courses will be focused on the theme.
Course Description / An introduction to basic concepts in probability and statistics. Topics include sampling techniques; data display; large and small sampling theory; binomial and normal probability distributions; and regression and correlation. Sample mean, standard deviation, confidence intervals, and hypothesis testing are introduced in business, economics and industrial contexts.
Prerequisite: MAT 012, MAT 013B, MAT 035 or equivalent placement
Note: Credit is not given for both MAT 223 and MAT 135 / Learn computing and information technology concepts and skills that are fundamental to social, personal, business, and academic environments. Topics include the Internet, networking, hardware, software, security, privacy, ethics, and emerging technologies. Hands-on lab experiences in word processing, spreadsheets, databases, and presentations are included using Microsoft Office applications.
Learning Objectives / Upon completion of this course, the student will be able to:
- Compute descriptive statistics and use them to organize data, and create and interpret graphs.
- Apply probability theory and solve problems using appropriate discrete or continuous probability distributions.
- Identify sampling techniques and model sampling distributions.
- Compute confidence intervals and lines of best-fit, and perform hypothesis tests for population means and proportions.
- Interpret and summarize statistical analyses using appropriate notation and terminology.
- Enter, display, and analyze data using technology.
8. Use statistics to analyze and interpret data.
9. Use results to draw conclusions and make decisions based on the comprehensive data analysis process.
10. Analyze their own exposure to bulk data collection and use that to inform their usage of social media and information technology.
11. Demonstrate their understanding of components of a computer system.
12. Evaluate their needs to buy a computer system.
13. Familiarize themselves with various networks and use of Internet.
14. Discuss capabilities of system and application software.
15. Familiarize themselves with ethical issues in using Internet and programming.
16. Discuss steps needed to keep their computer system secure
Required Materials / Textbook: Statistics: Informed Decisions Using Data, fourth edition, Michael Sullivan, III, Pearson Education, Inc. (Pearson Prentice Hall)
Supplemental materials will be provided relating to the theme.
Software: Microsoft Office, and various online tools. Students will need access to MyLabsPlus for homework.
Calculator: While a scientific calculator may be minimally adequate for completing this course, it is strongly recommended that students obtain a TI-83/84 calculator. Students may not use a TI emulator on their smartphones or tablets during exams. / Textbook:Computing Essentials 2017, O’Leary, et al. (2017). McGraw Hill Education.
Software: Microsoft Office 2016 (available through the MyAACC portal)
Attendance / Attendance is class is required of all students. We will be doing a number of in-class group activities, some of which will be extremely difficult to replicate by oneself outside of class. AACC faculty are required to report attendance daily. If you must miss class, you can submit assignments to me by email before the end of class (scan or take a clear photo). Late assignments will be assessed a 50% penalty. Exceptions to this policy will be made only under extreme circumstances, or if arrangements are made in advance of the absence. / CLASS ATTENDANCE IS REQUIRED. Students are expected to attend class regularly, to arrive for class on time, and to stay for the entire class. One point will be deducted from the final grade for each class missed.
Grading / Midterm Exams (x3) – 80 points each (240 points total)
Final Exam – 200 points
Online Homework – 125 points
Lab Projects – 230 points
Modeling Project – 50 points
Comprehensive Final Analysis Project – 75 points
Quizzes – 80 points
The total course grade is out of 1000 points. Grades will be awarded as follows:
F: 0-599 points
D: 600-699 points
C: 700-799 points
B: 800-899 points
A: 900+ points / Lab Assignments – 40%
Weekly Quizzes – 30%
Midterm Exam – 10%
Final Exam – 20%
A – 90% and above
B – 80 – 89%
C – 70 – 79%
D – 60- 69%
F – 59% and below
Exams / Exams will be given in class. Make-ups will be allowed if 1) prior permission is obtained and make-up time is scheduled in advance (more than 48 hours!), 2) under exceptional circumstances. Students are responsible for contacting me in a timely fashion. Once a graded exam is returned to students, the exam cannot be made up under any circumstances.
Final Exam: Wednesday, December 14th, 2016, 12:30-2:30 p.m.
The final exam is comprehensive, but will emphasize more recent material.
Midterm exam essay questions on the theme of the learning community will be administered on both exams, announced in advance, and will count as credit for exams in both courses. / Midterm exam and final exam will be taken in class and will be accessible through canvas. Makeup exams may be allowed if the student presents documentation for their absence more than 48 hours in advance. Makeup exams will be taken in the testing center. Once a graded exam is returned to students, it cannot be made up under any circumstance.
Final Exam: Monday, December 12th, 2016, 12:30-2:30 p.m.
The final exam is comprehensive, but will emphasize material presented after the mid-term.
Online Homework / Students will be required to complete homework problems in MyLabsPlus. Homework will be due in MyLabsPlus weekly. / All quizzes, exams, and lab assignments will be submitted through Canvas. No late assignments will be accepted.
Attendance and Participation / As noted above, faculty are required to report attendance to the college daily. You must attend 75% or more of classes to be consider “attending” for reporting purposes. Your grade for this component will be computed this way:
We will be doing a number of in-class activities to accompany learning in the classroom. Not fully participating in these activities may result in penalties up to 4 points for non-participation, not to exceed 5 points total for any one day. / As noted above, students are expected to attend class regularly, to arrive for class on time, and to stay for the entire class.
Students who do not engage in joint projects will receive lower grades than their peers.
Projects / Students will be completing a number of projects during the course of the semester. One project will be completed in class working in groups. There will be a number of joint CTA100/MAT135 technology projects throughout the term, which will count at credit for both courses. These projects will be announced in advance. More information on these projects will be forthcoming. While we will leave some time in class to work on the projects, expect to complete the bulk of the projects outside of class. Students may use any of the open math labs such as MATH 206 or CRSC 190, or other computer labs on campus for Office software. You can also download a current version of Office from your school email account. / There will be several lab projects done during class time on Wednesdays (and possibly Fridays) where you will hone your skills doing data analysis using tools on the internet and creating documents using Microsoft Office tools. Note that because you are enrolled as an AACC student, all campus labs are available to you.
Quizzes / In general, there will be a short in-class quiz once per week, generally on Friday, each one worth 8 points each. There are intended to give you some idea of the kinds of questions to expect on forthcoming exams, and to give you some idea of how I might ask questions different from/similar to the textbook. While more than 80 points will be theoretically available to account for missed quizzes, no more than 80 points may count toward the final course grade. Missed quizzes cannot be made up. / Every week there will be two or more quizzes in Canvas that will assess your knowledge of the computing concepts that were introduced in each book chapter. Missed quizzes cannot be retaken or submitted late.
Tutoring / Help with the material is available during my posted office hours, by appointment, or by email. You may also visit the Math Lab in Library 102 for additional assistance. It is recommended that you seek out help early and often rather than wait until you are in a hole difficult to climb out of. You can also receive assistance with the Office software from the tutoring lab in CALT. / If you need help with completing the in-class projects, using the tools in Microsoft Office, or any other software, please contact me to set up a meeting. I do not have a permanent campus office. A little help when students first get stuck can go a long way in keeping them out of an insurmountable hole.
Special Needs / Notice of Nondiscrimination: AACC is an equal opportunity, affirmative action, Title IX, ADA Title 504 compliant institution. Call Disability Support Services, 410-777-2306 or Maryland Relay 711, 72 hours in advance to request most accommodations. Requests for sign language interpreters, alternative format books or assistive technology require 30 days’ notice. For information on AACC’s compliance and complaints concerning sexual assault, sexual misconduct, discrimination or harassment, contact the federal compliance officer and Title IX coordinator at 410-777-1239, or Maryland Relay 711.
Disability Support Services Statement:
The Disability Support Services Office (DSS) provides equal access to educational opportunities for qualified students with disabilities. Students interested in course accommodations must provide relevant documentation in order to receive accommodations. For information, please call Courtney Sales, Program Manager for DSS, at 410.777.2306, email her r visit Deaf and hard of hearing students can reach the office by calling Maryland Relay 711 or by .
Technology in the Classroom / Please turn off all cell phones and other electronic devices while in class unless they are being used directly on a specific assignment. Use of these items is strictly forbidden during tests. If you wish to use a tablet or laptop for note-taking, you may ask permission to do so, but do not abuse the privilege by listening to music, watching videos, checking Facebook, or other non-class-related activities while class is going on. It is distracting to other students, and I will rescind permission to use your device in class if a student cannot stay on task. Be courteous to your peers. Do not text in class.
Calculators on phones and tablets are okay to use during in-class activities and for homework, however, they will not be permitted during in-class quizzes or during tests. Do not count on me having a spare for you to borrow.
Weather Policy / If the college is officially closed for any reason, the activities and material scheduled for the day on which the college was closed will be covered / take place during the next class meeting. This includes scheduled tests. Unless otherwise announced online homework due dates will still be in effect as officially scheduled. Sign up for emergency alert text messages at .
Academic Integrity / Academic honesty is expected at all times from all AACC students. There is never a reason to cheat, facilitate, plagiarize or otherwise not show integrity. Behavior violating the school’s Academic Integrity Policy will result in severe sanctions. They can range from zero points for the respective assignment/quiz/test to a failing class grade, and do not have to be limited to sanctions involving grades. Other sanctions, e. g. community service, can be imposed as well. If this is a repeat or even more severe offense, harsher penalties than failing the class may be given. Each violation of the Academic Integrity Policy will be formally put in an incident report and forwarded to the appropriate college representative. The complete academic integrity policy can be found in the online College Catalog – College Policies and Procedures – Academic Integrity Policy.
Student Opinion Forms / Toward the end of the semester you will be asked to fill out an online Student Opinion Form to provide feedback on your learning and your instructor’s teaching concerning this course. Your responses will be anonymous and your instructor will receive the results only after submitting final grades. Your input is important because it may offer information, recommendations, or ideas to improve teaching and learning at AACC. You can be assured that all comments will be read and taken into consideration to make this class the best it can be. Please follow the request to participate.
If 80% of the class completes the opinion survey, everyone will get 5 bonus points in MAT 135 and 2% in CTA 100.
The Greek alphabet
Letter name / Uppercase / Lowercase / Letter name / Uppercase / Lowercase
Alpha / / / Nu / /
Beta / / / Xi / /
Gamma / / / Omicron / /
Delta / / / Pi / /
Epsilon / / / Rho / /
Zeta / / / Sigma / /
Eta / / / Tau / /
Theta / / / Upsilon / /
Iota / / / Phi / /
Kappa / / / Chi / /
Lambda / / / Psi / /
Mu / / / Omega / /
Tentative Schedule
Week / Dates / Topics/Sections Covered / Comments/Due Dates
MAT 135 / CTA 100
1 / 8.29 / Introduction to the Course and Learning Community
1.1 Introduction to the Practice of Statistics, 1.2 Observational Studies vs. Designed Experiments, 1.3 Simple Random Sampling / Take Academic Integrity Quiz
Review Syllabus
8.31 / 1.4 Other Effective Sampling Methods, 1.5 Bias in Sampling,
1.6 The Design of Experiments / Pre-Test (not graded) and Lecture – History of Continuous Discontinuous Technical Innovations / Big Data Book: Read Introduction
9.2 / 2.1 Organizing Qualitative Data: Common Statistical Graphs and Online Tools, 2.2 Organizing Quantitative Data: The Popular Displays / Chapter 9: Privacy, Security and Ethics / Read: History of Big Data
Quiz #1 (135)
2 / 9.5 / No Class: Labor Day / MLP Sections 1.1-1.6 (135)
9.7 / 2.3 Additional Displays of Data
2.4 Graphical Misrepresentations of Data / Chapter 1: Information Technology, the Internet & You / Big Data Book: Read Chapter 1
9.9 / 3.1 Measures of Central Tendency
3.2 Measures of Dispersion3.3 Measures of Central Tendency & Dispersion from Grouped Data / CTA 100: Week 1 concept quizzes due 9/11
Quiz #2 (135)
3 / 9.12 / 3.4 Measure of Position and Outliers
3.5 The Five-Number Summary and Boxplots / MLP Sections 2.1-2.4, 3.1, 3.2 (135)
9.14 / Work on Project Day / Chapter 2: The Internet, the Web, and Electronic Commerce / Data Visualization Project (135)
Big Data Book: Read Chapter 2
9.16 / 4.1 Scatterplots and Correlation
4.2 Least Squares Regression
4.3 Diagnostics on the Least-Squares Regression Lines / CTA 100:Week 2 concept quizzes due 9/18
Quiz #3 (135)
4 / 9.19 / Monte Carlo Modeling Project Week / Chapter 3: Application Software / MLP Sections 3.3-3.5, 4.1-4.3 (135)
9.21 / Monte Carlo Modeling Project Week / Big Data Book: Read Chapter 3
9.23 / Monte Carlo Modeling Project Week / CTA 100:Week 3 Concept quizzes due 9/25
Quiz #4 (135)
5 / 9.26 / 5.1 Probability Rules
5.2 The Addition Rule and Complements
5.3 Independence and the Multiplication Rule / Chapter 4: System Software / Monte Carlo Project
9.28 / 5.4 Conditional Probability and the General Multiplication Rule
Review for Exam #1 / Big Data Book: Read Chapter 4
Quiz #5 (135)
9.30 / Exam #1 covers Chapters 1, 2, 3 and 4 / CTA 100: Week 5 Concept quizzes due 10/2
6 / 10.3 / 5.5 Counting Techniques
5.6 Putting it Together: Which Method Do I Use? / Chapter 5: The System Unit / MLP Sections 5.1-5.4 (135)
10.5 / 6.1 Discrete Random Variables / Big Data Book: Read Chapter 5
10.7 / Work on Project Day / Project: Privacy and Probability (135)
CTA 100: Week 6 Concept quizzes due 10/9
Quiz #6 (135)
7 / 10.10 / 6.2 Binomial Probability Distribution / Chapter 6: Input and Output / MLP Section 5.5-5.6, 6.1-6.2 (135)
10.12 / 7.1 Properties of the Normal Distribution 7.2 Applications of the Normal Distribution / Big Data Book: Read Chapter 6
10.14 / 7.3 Assessing Normality
7.4 The Normal Approximation to the Binomial Distribution / CTA 100: Week 7 Concept quizzes due 10/16
Quiz #7 (135)
8 / 10.17 / 8.1 Distributions of the Sample Mean / Midterm Review / MLP Sections 7.1-7.4 (135)
10.19 / Work on Project Day / Midterm Review / Big Data Book: Read Chapter 7
10.21 / Work on Project Day / Midterm Exam:
Chapters 1-6 and 9 / Project: Using Excel for Statistics (135)
Quiz #8 (135)
9 / 10.24 / 8.2 Distribution of Sample Proportions / Chapter 7: Secondary Storage / Big Data Book: Read Chapter 8
10.26 / Review for Exam #2 / Quiz #9 (135)
10.28 / Exam #2 covers Chapters 5, 6, 7 and 8 / CTA100: Week 9 concept quizzes due 10/30
10 / 10.31 / 9.1 Estimating a Population Proportion / Chapter 8: Communications and Networks / MLP Sections 8.1, 8.2 (135)
11.2 / 9.2 Estimating a Population Mean / Big Data Book: Read Chapter 9
11.4 / 9.4 Putting it Together: Which Procedure Do I Use? / CTA100: Week 10 concept quizzes due 11/6
Quiz #10 (135)
11 / 11.7 / 10.1 The Language of Hypothesis Testing / Chapter 11: Databases / MLP Sections 9.1, 9.2, 9.4 (135)
11.9 / 10.2 Hypothesis Tests for a Population Proportion, 10.3 Hypothesis Tests for a Population Mean / Big Data Book: Read Chapter 10
11.11 / 10.5 Putting it Together: Which Method Do I Use? 11.1 Inference About Two Population Proportions / Project: Databases & Big Data (135)
CTA100: Week11 concept quizzes due 11/13
Quiz #11 (135)
12 / 11.14 / 11.2 Inference About Two Population Means: Dependent Samples, 11.3 Inference About Two Population Means: Independent Samples / Chapter 10: Information Systems / MLP Sections 10.1-10.3, 10.5 (135)
11.16 / 11.5 Putting It Together: Which Method Do I Use? / Big Data Book: Read Chapter 11
11.18 / 12.1 Goodness of Fit Test
12.2 Tests of Independence & Homogeneity / CTA100: Week12 concept quizzes due 11/20
Quiz #12 (135)
13 / 11.21 / Review for Exam #3 / Chapter 12: Systems Analysis and Design / MLP Sections 11.1-11.3, 11.5 (135)
11.23 / Exam #3 covers Chapters 9, 10, 11, 12
11.25 / No class: Thanksgiving Holiday / CTA100: Week12 concept quizzes due 11/27
14 / 11.28 / Work on Project Day / Chapter 13: Programming and Languages / MLP Sections 12.1, 12.2 (135)