MATH 22: Statistics
Instructor:
Tom Greenwood
Office:
MS 102
Office Hours:
MWR 10:50 – 12, W 10:50 – 11:30, W 2:15 – 3:15, or by appointment.
Phone:
395-4229
E-Mail:
tgreenwo@bakersfieldcollege.edu
Website:
http://www2.bakersfieldcollege.edu/tgreenwood
Prerequisites:
A grade of “C” or better in Math D 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
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Chapter 7
Chapter 8
Chapter 9
Chapter 10
Chapter 11
Chapter 12
Chapter 13
Chapter 14
Chapter 15
Chapter 16
Grading:
Quizzes
Labs
Exams
Final Exam
Total
Introduction (1/2 week)
Experimental Design and Data Collection (1/2 week)
Graphical Displays of Univariate Data (1 week)
Measurements of Location and Position (1 week)
Measurements of Variability (1/2 week)
Probability (2 weeks)
Random Variables and Probability Distributions (1/2 week)
The Binomial Probability Distribution (1 week)
The Normal Distribution (1 week)
Sampling Distributions (1/2 week)
Confidence Intervals for Univariate Data (2 weeks)
Univariate Hypothesis Testing (1 week)
Difference Between Two Population Parameters (1 ½ weeks)
Analysis of Variance (1/2 week)
Categorical Data Analysis (1/2 week)
Correlation and Simple Linear Regression (1/2 week)
15%
15%
50%
20%
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 13 from 12 to 1:50 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 during class, you can 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 30, 2015
Last day to drop with a “W” is March 27, 2015
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).