Syllabus
Class: MA 115-D1, Fall 2013.
Instructor: Ivan Zaigralin.
Email: Go to http://melikamp.com/mew.php and type "show email".
Class Meetings: Tue, Thu 2:00pm-3:30pm in CAS B12.
Office Hours: Tue, Thu 4pm-5pm, in MCS 238.
Text: Sullivan: Statistics: Informed Decisions.... Some assigned homework may require online access (sold with the book).
Course Web Page:
http://www.melikamp.net/math/2013-09-ma-115.xhtml
The Web page will contain this syllabus, announcements, and the
assigned work. Check it before you email the instructor with
questions. To view the assigned homework online you may have to
use Mozilla
Firefox.
Official Description: MA 115 may not be taken for credit by any student who has completed any MA course numbered 300 or higher. Students may receive credit for not more than one of the following courses: CAS MA 113, MA 115, or MA 213. Numerical and graphical summaries of univariate and bivariate data. Basic probability, random variables, binomial distribution, normal distribution. One-sample statistical inference for normal means and binomial probabilities. Primarily for students in the social sciences with limited mathematics preparation. Carries MCS divisional credit in CAS.
Informal Description: This course serves as an introduction to basic concepts and tools in statistics and probability. We begin with how to describe data. Then we study the elements of probability theory. Finally, we combine data description and probability theory into an approach to statistical inference. Students should emerge from this course with the ability to incorporate a variety of skills in analyzing and reasoning from data.
Grading: 10% of the grade will be in the online homework, 10% in the offline homework, 25% in each of the two midterms, and 30% in the final. Additionally, some of the grade will be in worksheets (see below); not turning in the worksheets will result in a penalty of up to 5% of the total score.
Worksheets: Discussions will have time set aside for solving worksheet exercises while working in small groups. Separate this work from your lecture notes and other subjects, if any.
Final: Monday, December 16, 2013, 3pm-5pm.
Make-Ups: None, except for documented emergency exceptions made at the instructor’s discretion. A valid reason for missing a due date would be something like a documented case of a serious illness or a family emergency.
Last Day To Drop: Monday, October 7, 2013.
Last Day To Drop With 'W': Friday, November 8, 2013.
Academic Conduct: CAS Academic
Conduct Code is available for your perusal at
http://www.bu.edu/academics/cas/policies/academic-conduct/
A copy of the code is available in CAS 105 if you cannot access it
on the Web, and it is your responsibility to know and follow the
provisions of the code. In particular, all work that you submit in
this course must be your original work. Any cases of suspected
academic misconduct will be referred to the CAS Student Academic
Conduct Committee. Penalties for violating the Academic Conduct
Code may include suspension or expulsion from the University.
Help: If you need additional help, check out the Educational Resource Center. They offer peer tutoring free to BU students.
Plan:
Part I. Introduction to Statistics (Chapter 1).
Sec. 1.1. Introduction to the Practice of Statistics (p. 1-11)
Sec. 1.2. Observational Studies versus Designed Experiments (p. 15-19)
Sec. 1.3. Simple Random Sampling (p. 22-24)
Sec. 1.4. Other Effective Sampling Methods (p. 30-36).
Part II. Descriptive Statistics (Chapters 2 - 4).
Sec. 2.1. Organizing Qualitative Data (p. 65-73).
Sec. 2.2. Organizing Quantitative Data: The Popular Displays (p. 81-93)
Sec. 2.3. Additional Displays of Quantitative Data (p. 101- 104).
Chapter 3: Numerically Summarizing Data
Sec. 3.1. Measures of Central Tendency (p. 128- 135)
Sec. 3.2. Measures of Dispersion (p. 141- 151)
Sec. 3.4. Measures of Position and Outliers (p. 164 - 170)
Sec. 3.5. The Five-Number Summary and Boxplots (p. 174 - 178).
Chapter 4: Describing the Relation between Two Variables
Sec. 4.1. Scatter Diagrams and Correlation (p. 190 -199)
Sec. 4.2. Least-Squares Regression (p. 207 – 214) Appendix B, CD (p. B1-B5).
Part III. Probability (Chapters 5- 7).
Sec. 5.1. Probability Rules (p. 253 - 264).
Sec. 5.2. The Addition Rule and Complements (p. 269 - 276)
Sec. 5.3. Independence and the Multiplication Rule (p. 280 - 284).
Sec. 5.4. Conditional Probability and the General Multiplication Rule (p. 286 - 292).
Sec. 5.5. Counting Techniques (p. 296 - 304).
Chapter 6: Discrete Probability Distributions. The Binomial Distribution.
Sec. 6.1. Discrete Random Variables (p. 322 - 329).
Sec. 6.2. The Binomial Probability Distribution (p. 333 - 343)
Chapter 7: Continuous Probability Distributions. The Normal Distribution.
Sec. 7.1. Properties of the Normal Distribution (p. 361 - 366).
Sec. 7.2. Applications of the Normal Distribution (p. 370 - 377)
Sec. 7.4. The Normal Approximation to the Binomial Probability Distribution (p. 388 - 391).
Part IV. Statistical Inferences (Chapters 8 - 11).
Sec. 8.1. Distribution of the sample mean (p. 401 - 409).
Sec. 8.2. Distribution of the sample proportion (p. 413 - 418).
Chapter 9: Estimating the Value of a Parameter.
Sec. 9.1. Estimating a Population Proportion (p. 426 - 436).
Sec. 9.2 Estimating a Population Mean (p. 440 - 447).
Sec. 9.3. Estimating a Population Standard Deviation (p. 455 - 459).
Sec. 9.4. Putting It Together: Which Procedure Do I Use? (p. 461 – 462).
Chapter 10: Hypothesis Tests Regarding a Parameter.
Sec. 10.1. The Language of Hypothesis Testing (p. 477 - 482).
Sec. 10.2. Hypothesis Tests for a Population Proportion (p. 484 - 493).
Sec. 10.3. Hypothesis Tests for a Population Mean (p. 497 - 501).
Sec. 10.4. Hypothesis Tests for a Population Standard Deviation (p. 508 - 511).
Sec. 10.5. Putting It Together: Which Method Do I Use? (p. 514).
Chapter 11: Inferences on Two Samples.
Sec. 11.1. Inference about Two Population Proportions (p. 529 - 539).
Sec. 11.2. Inference about Two Means: Dependent Samples (p. 544 - 549).
Sec. 11.3. Inference about Two Means: Independent Samples (p. 554 - 560).
Sec. 11.5. Putting It Together: Which Method Do I Use? (p. 576 - 577).