MATH 155 Dr. Robert A. Johnson, Lecturer
Department of Mathematics and Computer Science,
CLASS POLICY
MATH 155 Modern Statistics with Computer Analysis
Sections: TR
TR
OFFICE: Henson Science Hall, Room 128 Phone: (410) 543 6469
OFFICE HOURS: 10 10:50 MWF
TEXTBOOK - A First Course in Statistics. By McClave and Sincich, Ninth Edition
COURSE DESCRIPTION: This is an introductory course in statistics emphasizing inference, with coverage of data collection and analysis needed to evaluate the results of statistical studies and make good decisions. It covers basic statistical and probability topics through simple linear regression. The course assumes a mathematical background of high school algebra. The statistical software Minitab will be used for lab assignments throughout this course.
COURSE EVALUATION: The final grade in the course will be based on 400 points, which is the total
number of points that can be accumulated in this course (excluding extra points). The following shows how points can be earned.
A. Homework and Quizzes (15% - 60 points) Problems will be assigned on a regular basis and selected ones will be graded. There will be weekly quizzes.
B. Chapter Exams (50% - 200 points) There will be a exam after the completion of each chapter.
C. Final Exam (25% - 100 points) a comprehensive final exam will be given. As part of the final exam, a critique of a formal research is required.
D. Lab Assignments (10% - 40 points) Problems involving the use of MINITAB will be assigned.
E. Extra Credit Challenging exercises will be assigned throughout the semester for bonus points.
Final Grade Intervals
400 360 A
359 320 B
319 280 C
279 240 D
Below 240 F
ATTENDANCE POLICY Attendance is required. More than three unexcused absences may lower final grade.
WEEKLY SCHEDULE OF DISCUSSION TOPICS AND HOMEWORK
MATH 155 Modern Statistics with Computer Analysis
Week 1
Chapter 1 Statistics, Data, and Statistical Thinking
1.1 The Science of Statistics
1.2 Types of Statistical Applications
1.3 Fundamental Elements of Statistics
1.4 Types of Data
1.5 Collecting Data
1.6 The Role of Statistics in Critical Thinking
Exercises 1.12, 1.15, 1.16, 1.18, 1.22, 1.25, 1.28
Week 2
Chapter 2
2.1 Describing Qualitative Data
Exercises 2.4, 2.5, 2.7, 2.13, 2.14
2.2 Graphical Methods for Describing Quantitative Data
Exercises 2.23, 2.24, 2.27, 2.35
2.3 Summation Notation
Exercises 2.38, 2.39, 2.40, 2.41
2.4 Numerical Measures of Central Tendency
Exercises 2.49, 2.52, 2.56, 2.59
2.5 Numerical Measures of Variability
Exercises 2.68 2.70, 2.72, 2.78
2.6 Interpreting the Standard Deviation
Exercises 2.82, 2.84, 2.87, 2.8
Week 3
2.7
2.8 Numerical Measures of Relative Standing
Exercises 2.101, 2.106, 2.109
2.9 Methods for Detecting Outliers
Exercises 2.120, 2.124
Exam (Chapters 1 and 2)
Week 4
Chapter 3 - Probability
3.1 Events, Sample Spaces and Probability
Exercises 3.10, 3.12, 3.23, 3.24
3.2
3.3 Complementary Events
3.4 The Additive Rule and Mutually Exclusive Events
Exercises 3.41, 3.42, 3.44, 3.48, 3.52
3.5 Conditional Probability
3.6 The Multiplicative Rule and Independent Events
Exercises 3.66, 3.68, 3.70, 3.75
Week 5
3.6 Random Sampling
Exercises 3.95 3.96
Exam (Chapter 3)
Chapter 4 Random Variables and Probability Distributions
4.1 Two Types of Random Variables
Exercises 4.4, 4.5
4.2 Probability Distributions for Discrete Random Variables
Exercises - 4.13, 4.14, 4.18, 4.22
Week 6
4.3 The Binomial Random Variable
Exercises - 4.38, 4.48, 4.49, 4.5
4.4 Probability Distributions for Continuous Random Variables
4.5 The Normal Distribution
Exercises - 4.62,4.69, 4.71, 4.73, 4.74
4.6 Descriptive Methods for Assessing Normality
Exercises 4.91, 4.93, 4.96
Week 7
4.8 Sampling Distributions
Exercises - 4.120, 4.123
4.9 The Central Limit Theorem
Exercises - 4.135, 4.137, 4.140
Exam (Chapter 4)
Chapter 5 - Inferences Based on a Single Sample
5.1 Identifying the Target Parameter
5.2 Large-Sample Confidence Interval
Exercises 5.8, 5.10, 5.13, 5.14, 5.6
Week 8
5.3 Small-Sample Confidence Interval for a Population Mean
Exercises 5.28, 5.29, 5.31, 5.32, 5.34, 5.35
5.4 Large-Sample Confidence Interval for a Population Proportion
Exercises 5.45, 5.46, 5.47, 5.49
5.5 Determining the Sample Size
Exam (Chapter 5)
Chapter 6 Influences Based on a Single Sample
6.1 The Elements of a Test of Hypothesis
Exercises 6.8, 6.11, 6.13
Week 9
6.2 Large-Sample Test of Hypothesis about a Population Mean
Exercises - 6.22, 6.24, 6.24. 6.26
6.3 Observed Significance
Exercises 6.38, 6.45, 6.46, 6.47
6.4 Small-Sample Test of Hypothesis about a Population Mean
Exercises 6.57, 6.58, 6.61, 6.62
6.5 Large-Sample Test of Hypothesis about Population Proportion
Exercises 6.76, 6.79, 6.82
Week 10
Exam (Chapter 6)
Chapter 7 Comparing Population Means
7.1 Comparing Two Population Means: Independent Sampling
Exercises 7.3, 7.5, 7.8,7.11
7.2 Comparing Two Population Means: Paired Difference Experiments
Exercises 7.30, 7.32, 7.37
Week 11
7.3 Finding the Sample Sizes for Estimating M M
Exercises 7.48, 7.51
Exam (Chapter 7)
Chapter 8 Comparing Population Proportions
8.1 Comparing Two Population Proportions: Independent Sampling
Exercises 8.4, 8.6, 8.10, 8.13
Week 12
8.2 Determining the Sample Size
Exercises 8.24, 8,25, 8.27
8.3 Testing Categorical Probabilities: Multinomial Experiment
Exercises 8.33, 8,37, 8,39, 8,40
8.4 Testing Categorical Probabilities: Two-Way (Contingency) Table
Exercises 8.51, 8.52, 8.56, 8.59
Week 13
Exam (Chapter 8)
Review for final exam