Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Foundations of statistics wikipedia , lookup
Bootstrapping (statistics) wikipedia , lookup
Degrees of freedom (statistics) wikipedia , lookup
Confidence interval wikipedia , lookup
History of statistics wikipedia , lookup
Taylor's law wikipedia , lookup
Resampling (statistics) wikipedia , lookup
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!! 2 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 4 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