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Hill College 112 Lamar Dr. Hillsboro, Texas 76645 COURSE SYLLABUS Course Prefix and Number Course Title MATH 1342 STATISTICS Prepared by: T. CALHOUN Date: August 2013 Approved by: Date: Dean of Instruction Approved by: Date: Vice President of Instruction D i s a b i l i t i e s / AD A In accordance with the requirements of the Americans with Disabilities Act (ADA) and the regulations published by the United States Department of Justice 28 C.F.R. 35.107(a), Hill College’s designated ADA coordinator, Melanie Betz, Director of Academic Advising & Student Success, shall be responsible for coordinating the College’s efforts to comply with and carry out its responsibilities under ADA. Students with disabilities requiring physical, classroom, or testing accommodations should contact the Director of Academic Advising & Student Success, at (254)659-7651. Course Description: MATH 1342 Collection, analysis, presentation, and interpretation of data and probability. Analysis includes descriptive statistics, correlation and regression, confidence intervals and hypothesis testing. Use of appropriate technology is recommended. Lecture Hours 3 Lab Hours 0 Semester Credit Hours 3 Prerequisites: None Introduction and Purpose This course provides a one-semester general course in introductory statistics. To exemplify the broad applications of both descriptive statistics and statistical inference, illustrations will be drawn from the social sciences, agriculture, medicine, ecology, law enforcement, and other areas. Instructional Materials Textbook: Fundamentals of Statistics (4th. ed.); Sullivan; Prentice Hall. Supplies: Notebook paper, graph paper, ruler, and graphing calculator. Objectives/Student Learning Outcomes At the completion of this course the student should be able to: 1. Explain the use of data collection and statistics as tools to reach reasonable conclusions. 2. Recognize, examine and interpret the basic principles of describing and presenting data. 3. Compute and interpret empirical and theoretical probabilities using the rules of probabilities and combinatorics. 4. Explain the role of probability in statistics. 5. Examine, analyze and compare various sampling distributions for both discrete and continuous random variables. 6. Describe and compute confidence intervals. 7. Solve linear regression and correlation problems. 8. Perform hypothesis testing using statistical methods. The students' success in completing these objectives will be measured using a set of examinations and assignments described, in detail under the section of this syllabus headed “Method of Evaluation”. Methods of Instruction This course will be taught face-to-face and by various distance learning delivery methods. Audio-visual materials and computer-based technology will be used when appropriate. Students will be shown how to use a calculator where appropriate. Method of Evaluation Grades in this course will be based on the following evaluative criteria: Major tests will be given. They will comprise 75% of the semester grade. A comprehensive final examination will be given. It will comprise 25% of the semester grade. Semester grades will be based on the following values: 90-100% 80-89% 70-79% 60-69% Below 60% A B C D F Class Policies: Regular attendance at all class meetings is expected. Disruptions in class will not be tolerated. Topic Outline: PART I. GETTING THE INFORMATION YOU NEED 1. Data Collection 1.1 Introduction to the Practice of Statistics 1.2 Observational Studies and Experiments 1.3 Simple Random Sampling 1.4 Other Effective Sampling Methods 1.5 Bias in Sampling 1.6 The Design of Experiments PART II: DESCRIPTIVE STATISTICS 2. Creating Tables and Drawing Pictures of Data 2.1 Organizing Qualitative Data 2.2 Organizing Quantitative Data 2.3 Graphical Misrepresentations of Data 3. Numerically Summarizing Data 3.1 Measures of Central Tendency 3.2 Measures of Dispersion 3.3 Measures of Central Tendency and Dispersion from Grouped Data 3.4 Measures of Position and Outliers 3.5 The Five-Number Summary and Boxplots 4. Describing the Relation Between Two Variables 4.1 Scatter Diagrams and Correlation 4.2 Least-Squares Regression 4.3 The Coefficient of Determination 4.4 Contingency Tables and Association PART III: PROBABILITY AND PROBABILITY DISTRIBUTIONS 5. Probability 5.1 Probability Rules 5.2 The Addition Rule and Complements 5.3 Independence and the Multiplication Rule 5.4 Conditional Probability and the General Multiplication Rule 5.5 Counting Techniques 5.6 Putting It Together: Probability 6. Discrete Probability Distributions 6.1 Discrete Random Variables 6.2 The Binomial Probability Distribution 7. The Normal Probability Distribution 7.1 Properties of the Normal Distribution 7.2 Applications of the Normal Distribution 7.3 Assessing Normality 7.4 The Normal Approximation to the Binomial Probability Distribution PART IV: INFERENCE–FROM SAMPLES TO POPULATION 8. Sampling Distributions 8.1 Distribution of the Sample Mean 8.2 Distribution of the Sample Proportion 9. Estimating the Value of a Parameter (Confidence Intervals) 9.1 Estimating a Population Proportion 9.2 Estimating a Population Mean Deviation is Unknown 9.3 Putting It Together: Which Method Do I Use? 10. Hypothesis Tests Regarding a Parameter 10.1 The Language of Hypothesis Testing 10.2 Hypothesis Tests for a Population Proportion 10.3 Hypothesis Tests for a Population Mean 10.4 Putting It Together: Which Method Do I Use? 11. Inference on Two Samples 11.1 Inference about Two Proportions 11.2 Inference about Two Means: Dependent Samples 11.3 Inference about Two Means: Independent Samples 11.4 Putting It Together: Which Method Do I Use? 12. Additional Inferential Procedures 12.1 Goodness of Fit Test 12.2 Tests for Independence and the Homogeneity of Proportions 12.3 Testing the Significance of the Least-Squares Regression Model 12.4 Confidence and Prediction Intervals Bibliography Sullivan, Michael III, Fundamentals of Statistics Informed Decisions Using Data (4th. ed.); Pearson/Prentice Hall, 2014, 2011, 2008