MATH 1: Math Analysis
MATH 22: Statistics
Instructor: Tom Greenwood
Office: MS 102
Office Hours: T 1:30 – 2:30, W 1:30 – 3:15, TH 2:00 – 3:15 or by appointment.
Phone: 395-4229
E-Mail:
Website: http://www2.bakersfieldcollege.edu/tgreenwood
Prerequisites: A grade of “C” or better in Math 70 or equivalent placement
Required Textbook: Data Analysis: An Applied Approach to Statistics with
Technology , 3rd edition, Jean, Meyers, and Sporer.
Course Description: Tabular, graphical, and numerical methods of summarizing data, finite probability, discrete and continuous random variables, binomial probability distribution, normal probability distribution, sampling distributions, point and interval estimation, one and two sample hypothesis testing procedures, analysis of variance, chi-square analysis, linear regression and correlation, and if time allows, nonparametric methods.
Course Content: Chapter 1 Introduction (1/2 week)
Chapter 2 Experimental Design and Data Collection (1/2 week)
Chapter 3 Graphical Displays of Univariate Data (1 week)
Chapter 4 Measurements of Location and Position (1 week)
Chapter 5 Measurements of Variability (1/2 week)
Chapter 6 Probability (2 weeks)
Chapter 7 Random Variables and Probability Distributions (1/2 week)
Chapter 8 The Binomial Probability Distribution (1 week)
Chapter 9 The Normal Distribution (1 week)
Chapter 10 Sampling Distributions (1/2 week)
Chapter 11 Confidence Intervals for Univariate Data (2 weeks)
Chapter 12 Univariate Hypothesis Testing (1 week)
Chapter 13 Difference Between Two Population Parameters (1 ½ weeks)
Chapter 14 Analysis of Variance (1/2 week)
Chapter 15 Categorical Data Analysis (1/2 week)
Chapter 16 Correlation and Simple Linear Regression (1/2 week)
Grading: Quizzes 15%
Labs 15%
Exams 50%
Final Exam 20%
Total 100%
Grades will closely follow this trend.
Percent Grade
90-100 A
80-89 B
70-79 C
60-69 D
Below 60 F
The overall grade is based on a percentage, not on points.
Homework: Homework will be assigned, but not be collected. The quizzes are based squarely on the assignments. Note that doing the homework helps in succeeding in this class.
Quizzes: Quizzes are based on the homework problems and labs. Quizzes are always announced in advance.
Labs: Data analysis labs will be assigned over the course of the semester. You will have a specific amount of time to complete each lab. These labs will be turned in on the specified due date. Late lab assignments will not be accepted. If you are not present on the day of the lab, you will not be able to make it up.
Exams: There will be an exam after every three to five chapters depending on the depth of the material.
Final Exam: This is a cumulative final.
The final is on Wednesday, May 11 from 10 to 11:50 pm.
Attendance: If you miss more than 8 classes, you will automatically be dropped from the class. I need not warn you when you are close to this point. Students cannot leave class early unless they have the professor’s permission prior to the start of class.
Makeups: There will be no makeup exams allowed. If you know that you are going to miss the exam in advance, please talk with me about making arrangements.
Calculators: The TI – 83/84 graphing calculator is required for this course. Graphing calculators are a good learning tool and the statistical functions on the TI – 83/84 help a great deal when we are doing data analysis.
Cheating: There will be a zero tolerance policy on cheating. A first offense will receive a zero on that assignment/quiz/exam and possible mention on their permanent record. A second offense will receive more drastic measures with a possibility of being removed from the course. Calculators are subject to being reviewed by the professor before, during, and after an examination. This is due to previous encounters in past semesters.
On quiz and exam days, if you need to use the bathroom or leave the class, you must leave your phone at my desk while you are outside the classroom.
Classroom Etiquette:
It is expected that you devote your full attention to the class. Some examples of bad etiquette are (but not limited to):
· Text messaging
· Reading newspapers, magazine, or other material not related to the class
· Talking
· Sleeping
· Studying for another class
Talking: There is absolutely no talking aloud while the professor is conducting lecture. This is a distraction to not just the professor, but fellow students as well. Please have consideration for the students around you. Failure to do so will result in being asked to leave the class.
Sleeping: Sleeping is not permitted in class. If you cannot stay awake in class……go home and get some rest.
Cell Phones: Cell phones need to be either turned off for the duration of class. It is unacceptable to answer the phone either in class or to leave class to take a phone call. Any use of the cell phone in class will result in you being asked to leave the class. No exceptions.
Texting: Texting in class is prohibited. This is the equivalent to talking in class. If you caught texting, or using your cell phone, during class, you will be asked to leave the class.
Electronic Devices: Electronic devices (i.e. iPod, cell phone, laptop, etc.) should be turned off and put away before the beginning of class. Any electronic device being used in class can also result in you being asked to leave the class.
Important Dates: Last day to drop without a “W” is January 31, 2016.
Last day to drop with a “W” is April 1, 2016.
Accommodations: Students with disabilities who believe they may need accommodations in this class are encouraged to contact Supportive Services on the first floor of the counseling building, 395-4334, as soon as possible to better ensure such accommodations are implemented in a timely manner.
FERPA: The Family Education Rights and Privacy Act (FERPA) is a federal law that prohibits the instructor from sharing student information (grades, class progress, etc..) with anybody except the student. This means that I cannot share your information with family members (parents, siblings, spouses, etc…).
Tutoring: Drop in tutoring is available in the Math Learning Center (Second floor of the Student Services Building). Tutoring by appointment is also available on the top floor of Student Services building.
Notes: This is not an algebra class. Most of the material that we will cover will be the first time that most of you have seen it. It is strongly recommended that you attend all classes. Since this is new material, don’t ever be afraid to ask questions or ask for help from me.
Math 22 Student Learning Outcomes
1. The student will be able to understand statistical terminology and symbols.
2. The student will be able to construct and interpret graphs to display and classify data.
3. The student will compute and interpret appropriate descriptive statistics.
4. Compute probabilities using the basic probability laws.
5. Compute probabilities based on the binominal or normal distribution.
6. Recognize the importance, limitations, and applications of the Central Limit Theorem.
7. Describe and utilize sampling distributions.
8. The student will be able to construct and interpret the appropriate confidence interval.
9. The student will be able to construct and interpret the appropriate hypothesis test.
10. Use regression analysis to construct appropriate models on dependent quantitative variables.
11. Choose and apply appropriate inferential analyses to real situations in order to draw conclusions about a population(s).