STA 2023 – Fall 2011-1 InterAmerican Campus Instructor: Dr. Jose Serpa e-mail: [email protected] Office: 1369 Website: //faculty.mdc.edu/jserpa/ Reference Number: 655826 Class Times: Monday, Wednesday & Friday 8:00 a.m – 8:50 a.m Room #: 1127 Textbook: Elementary Statistics; M. F. Triola. 11th Edition Addison-Wesley Publishing Co. Course Objectives: Students in this course will acquire knowledge in the following topics: Collecting, grouping, and presenting data; measures of central tendency and dispersion; probability; estimation and hypothesis testing, linear correlation and regression. Competencies: At the end of the course the student should be able to: a) Identify the population and the sample in an inferential study. b) Construct data tables, histograms, dot-plots, pie charts, bar graphs, stem-and-leaf diagrams. c) Compute and interpret the mean, the median, the mode, and the standard deviation of a data set. d) Determine and interpret the quartiles, deciles and percentiles of a data set. Construct and interpret a box-and whisker diagram. e) Construct probability distributions, and compute conditional probabilities. f) Apply the binomial and normal distributions. g) Determine confidence intervals and sample sizes. h) Conduct hypotheses testing. i) Basic concepts of regression and correlation. Software: STATDISK (provided by the book) and Excel could be used in class and in some suggested problems assignment. Campus Math Lab: Students can obtain assistance from statistics tutors that can help you to successfully complete this course. The Math Lab is located at office # 1375. Phone : 305-237- 6116 . Classroom Policies: - Professional behavior is expected at all times. - Attendance is required for every class. The student will be purged from the class roster if he/her has more than two unexcused absences during the entire semester. - Beepers and cellular phones are not allowed in the class-room and during tests/exam. - Cell phones‟ calculators are not allowed to be used as calculators during tests/exam.Grading Policy: - There will be five tests worth 100 points each and a comprehensive mandatory Final Exam. HW will be posted online and will count as extra credits 10 points each. The lowest grade among all five tests will be dropped. There will be no makeups. The Final Exam may NOT be dropped. Your final grade will be based on the average of your four best test scores and the Final Exam. I may assign the seating during any of the tests or Final Exam. - Drops or Withdrawals: If you stop attending class, you must drop the class yourself to avoid a grade of „F‟. Grading Scale: A: 90 – 100 B: 80 – 89 C: 70 –79 D: 60 – 69 F: 0 - 59 Incompletes: Incompletes will be given in very limited situations. In order to qualify for an “I” grade, the student must be passing the course at the time the “I” grade is negotiated; be so near the end of the course that he/she requires no further instruction; and have a justifiable and documented reason for not being able to finish the course on schedule. Learning Outcomes: The competencies and objectives included in this course will address some of the recently adopted Miami Dade College General outcomes, a set of 10 learning outcomes we expect graduating students to master in the years to come. As graduate of Miami Dade College, students will be able to: 1. Communicate effectively using listening, speaking, reading, and writing skills. 2. Use quantitative analytical skills to evaluate and process numerical data. 3. Solve problems using critical and creative thinking and scientific reasoning. 4. Formulate strategies to locate, evaluate, and apply information. 5. Demonstrate knowledge of diverse cultures, including global and historical perspectives. 6. Create strategies that can be used to fulfill personal, civic, and social responsibilities. 7. Demonstrate knowledge of ethical thinking and its applications to issues in society. 8. Use computer and emerging technologies effectively. 9. Demonstrate an appreciation for aesthetics and creative activities. 10. Describe how natural systems function and recognize the impact of humans on the environment. The learning activities designed in this course will address outcomes 1, 2, 3, 4, 8 & 10. Tentative Class Schedule: Week Topics to be Covered 1 Types of Data. Methods to Collect Data. Frequency Distributions. 2 Frequency Distributions. Histograms. Statistical Graphics. Measures of Center Measures of Variation. Measures of Relative Standing. 3 ReviewTest #1. 4 Exploratory Data Analysis. Probability. Fundamentals Addition Rule 5 Multiplication Rule. Complements and Conditional Probabilities. Conditional Probabilities. Counting Rules. 6 Review Test #2 Random Variables. 7 Expected Value of a Discrete Random Value. Variance, Standard Deviation of a Discrete Random Variable. Binomial Probability Distribution. Mean, Variance and Standard Deviation for the Binomial Distribution. 8 Continuous Random Variable. The Standard Normal Distribution. Applications of Normal Distribution. 9 Review Test #3 Sampling Distributions. Estimators. 10 The Central Limit Theorem. Estimating a Population Proportion. Confidence Interval and Sample Size for P. 11 Estimating a Population Mean ( σ Known) Estimating a Population Mean (σ Unknown) Confidence Intervals for the population Mean. Sample Size. Margin of Error. 12 Review Test # 4 13 Basic of Hypothesis Testing Testing a Claim about a Proportion. Testing a Claim about a Mean (σ Known) Testing a Claim about a Mean (σ Unknown) 14 Introduction to Regression. Basic Concepts. Interpreting the Regression Equation Estimations. 15 Review Test #5 Basic Concepts of Correlation. 16 Correlation Coefficient. Correlation Analysis. Review for the final Exam. 17 Final Exam. Changes can be made. Any changes will be announced in class as early as