Download 1 Math 115 Statistical Reasoning Departmental Syllabus Spring

1
Math 115 Statistical Reasoning Departmental Syllabus
Spring 2011
Instructor: Ken Bonee
Office: 130 Ayres Hall
Office Hours: 10:10-11 MWF (1st floor of Undergrad Library)
9-12 T, 130 Ayres Hall
Email:
[email protected]
Webpage: http://www.math.utk.edu/~kbonee
Course
115.010
115.009
115.011
Section
20433
20432
20434
Time
8:00 – 8:50
11:15-12:05
12:20 - 1:10
Days
MWF
MWF
MWF
Location
HBB 113
HSS 57
HSS 57
Final Exam
8:00 – 10:00 Friday May 6
2:45 – 4:45 Tuesday May 3
8:00 – 10:00 Monday May 9
Course Description: An introduction to probability and statistics without calculus.
Not available for credit to students in the College of Business Administration. (QR) 3
credit hours.
Text: Essentials of Statistics, by Triola, Fourth Edition, Addison Wesley Publishers.
Calculator: A graphing calculator is required for this course. The Math Department
highly recommends and provides support for the TI-83+ and TI-84+ models, you will
need one of these models or another calculator capable of doing all required functions
for this course. Use of cell phone calculators and calculators with advanced alphanumeric capabilities, such as the TI-89, is forbidden in this course.
Grades: Grades will be determined using the grading scale below. Your letter grade is a
measure of your mastery of course material and your fulfillment of course objectives.
The “other*” category will consist of Homework & Project. MyMathLab homework will be
worth 50 points (explanation in class) and a project worth 50 points, for 100 points
total.
Exam 1
Exam 2
Exam 3
Other*
Final Exam
100 points
100 points
100 points
100 points
100 points
Total: 500 points
Letter grade: Range of scores:
A
448 - 500
A433 - 447
B+
413 - 432
B
398 - 412
B383 – 397
C+
363 - 382
C
348 - 362
C333 - 347
D+
313 - 332
D
298 - 312
D283 - 297
F
Below 282
Info for logging into MyMathLab will be given in class!!
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Important Dates:
Add/drop without W deadline
Spring Break No Class
Drop with W deadline
Drop with WP/WF deadline
Spring Recess No Class
Exam 1
Exam 2
Exam 3
Last day of classes
January 21
March 14-18
March 21
April 5
April 22
April 29
Final Exam: The final exam is comprehensive, and all students are required to take the
final exam. If you do not take the Final Exam you will fail the course!
Attendance: Will be taken daily. You will be held responsible for all material covered in
class. This includes, but is not limited to homework assignments, quizzes and exam
date announcements.
Make up exams: If any of the Exams are missed, you will have 1 (one) week to schedule a
make-up exam. Note: Since you will have had longer to prepare for the make-up exam it
will be different from the regular exam..
Disability Services: If you need course adaptations or accommodations because of a
documented disability or if you have emergency information to share, please contact the
Office of Disability Services at Dunford Hall, 974-6087.
Math Tutorial Center: The Math Tutorial Center is in Temple 109. It provides free
tutoring. Hours of operation are posted at http://www.math.utk.edu/MTC/. Please
make use of this free service.
Classroom Etiquette: Please be considerate of the instructor and those around you.
Come to class on time and stay the entire period. Turn off cell phones and beepers
during class. Do not talk to classmates at inappropriate times. Refrain from reading
newspapers or working on other coursework during class.
Academic Standards of Conduct:
All students are expected to abide by the University Honor Statement. In mathematics
classes, violations of the honor statement include copying another person's work on any
graded assignment or test, collaborating on a graded assignment without the
instructor's approval, using unauthorized "cheat sheets" or technical devices such as
calculators, cell phones or computers for graded tests or assignments, or other
infractions listed in "Hilltopics". These violations are serious offenses, subject to
disciplinary action that may include failure in a course and/or dismissal from the
University. The instructor has full authority to suspend a student from his/her class, to
assign an "F" in an exercise or examination, or to assign an "F" in the course. See
3
"Hilltopics" for more complete information. A report of all offenses will be sent to
appropriate deans and the Office Student Judicial Affairs for possible further action.
The Honor Statement
An essential feature of the University of Tennessee is a commitment to
maintaining an atmosphere of intellectual integrity and academic honesty. As
a student of the University, I pledge that I will neither knowingly give nor
receive any inappropriate assistance in academic work, thus affirming my own
personal commitment to honor and integrity.
Math 115 Homework list for Spring 2011
Section
1.2
Types of Data
1.3
1.4
2.2
2.3
2.4
3.2
3.3
3.4
3.5
4.2
4.3
4.4
4.5
5.2
Critical Thinking
Design of Experiments
Frequency Distributions
Histograms
Statistical graphs
Measures of Center
Measures of Variation
Measures of Relative Standing
Exploratory data analysis
Fundamentals of Probability
Addition Rule
Multiplication Rule
Complements and conditional Probability
Random Variables
6.2
The Standard Normal Distribution
6.3
6.4
6.5
7.2
7.3
7.4
7.5
8.2
8.3
8.4
8.5
8.6
10.2
10.3
11.2
11.3
Applications of Nonstandard
Normal Distributions
Sampling Distributions
The Central Limit Theorem
Estimating a Population Proportion
Estimating a Pop. Mean: Known
Estimating a Population Mean: Not Known
Estimating a Population Variance
Basics of Hypothesis Testing
Testing a Claim About a Proportion
Testing Claims About : Known
Testing Claims About : Not Known
Testing Claims About Variances and SD’s
Correlation
Regression
Multinomial experiments:
Contingency Tables:
Goodness of Fit
Test of Independence
Suggested Homework
1-12, 13-24
Identify as Quantitative or
Qualitative only
5-12, 21-26
5-8, 13-30
9-16
1-7
5, 6, 15, 17
1-4, 7, 8, 14, 18
7, 8, 14, 18, 33,
12-14
1-6
1-9, 17-20
8-12, 21-24
7-9, 15-20
7, 8, 12, 13, 18, 19, 21-24
6, 8, 10, 12, 19, 20
5-8, 12, 15, 18, 21, 24, 27,
29-39 and handout for
student’s t and
Chi-squared dist. P. 69
13-20
1-7 all
6-9, 12, 17
Handout with mixed
Set of problems p. 70/71
Handout with mixed
Set of problems
Hw #1 p. 72
Hw #2 p. 77-76
Handout with mixed
Set of problems p. 77-79
5, 6, 9, 12, 18, 21, 23
9, 10, 17, 22
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Math 115 symbols
x
a data value or a value from a
population
f
frequency
n
Sample size
N
Population size
n!
n factorial =
First quartile
Uppercase sigma, “sum up”
Second Quartile
Sum of the values
Third Quartile
Sample mean
Mu, Population mean
Sample standard deviation
Lower case Sigma, Population
standard deviation
Sample Variance
Population Variance
Sample proportion
Population proportion
Significance level, usually .05 or .01
Z
k
df
The number of degrees of freedom
Standard normal distribution or a
“Z-score”
Confidence interval limits based on
Z-scores
The student’s t distribution with n
degrees of freedom
Confidence interval limits based on
t-scores
Chi-squared distribution with n
degrees of freedom
Left confidence interval limit based
on a Chi-squared distribution
Sample coefficient of determination
Right confidence interval limit based
on a Chi-squared distribution
Pearson’s correlation coefficient for a
sample
Rho, Pearson’s correlation coefficient
for a population
Null hypothesis
Alternative hypothesis
The number of categories for a
qualitative or categorical variable
The predicted value of y
5
List of formulas
6
Confidence Intervals and hypothesis Tests
Parameter
Of
Interest
Is
Normal
Known? Pop.?
Yes
Sample
Size
Sampling
Distribution/
Test Statistic
T
Confidence Interval
Formulas
N/A
Do Not try this at home!!!!
Any
Yes
No
n>30
n<30
Close
To
***
Any
No
Not
Close
N/A
N/A
NO!!!!
YES!!
N/A
N/A
N/A
Use Nonparametric
methods
Any
Any
***Mathematically, we should be using the t-distribution here, and most software
packages will use it. The more degrees of freedom you have, the closer the values of the
t-distribution are to the values of the standard normal distribution, therefore
interchanging those values causes relatively little error. The errors you get from using
poor sampling techniques will cause much more trouble than will the fudging of
t-scores.
7
8
9
10