# PELLISSIPPI STATE COMMUNITY COLLEGE MASTER SYLLABUS INTRODUCTION TO STATISTICS MATH 2050

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1 PELLISSIPPI STATE COMMUNITY COLLEGE MASTER SYLLABUS INTRODUCTION TO STATISTICS MATH 2050 Class Hours: 2.0 Credit Hours: 3.0 Laboratory Hours: 2.0 Date Revised: Fall 2013 Catalog Course Description: Descriptive statistics, including bivariate trends; time series; concepts of probability and probability distributions; binomial and normal distributions; linear correlation and regression; estimation and significance tests for means; contingency tables, chi-square tests for goodness of fit and independence. A computer laboratory component is required. Entry Level Standards: A thorough knowledge of algebraic functions is necessary for entrance to this course. Students should be able to read and write on the college level and reason logically. Prerequisite: MATH 1830 or MATH 1910 Textbook(s) and Other Reference Materials Basic to the Course: Textbook: Larose, Discovering Statistics. W. H. Freeman, References: Triola, Mario F. Elementary Statistics. 9th ed. Redwood City, CA: The Benjamin/Cummings Publishing Company, Inc., Personal Equipment: According to instructor preference, you are allowed to use a calculator with statistical functions, Excel software, or a combination of the two.

2 I. Week/Unit/Topic Basis: Week Topic 1 Statistical applications in business and economics; data; data sources; descriptive statistics; statistical inference and probability; summarizing qualitative data. Chapters 1 and 2 2 Summarizing quantitative data; exploratory data analysis; cross-tabulations and scatter diagrams. Chapter 3 3 Measures of location; measures of variability; some uses of the mean and the standard deviation; exploratory data analysis; measures of the association between two variables; computing measures of location and dispersion for grouped data. Chapter 3 4 Experiments, the sample space, and counting rules. Chapter 4 5 Assigning probabilities to experimental outcomes; events and their probabilities; some basic relationships of probability; conditional probability; random variables. Chapter 4 6 Discrete probability distributions; expected value and variance; the binomial probability distribution; the uniform probability distribution. Chapter 5 7 The normal probability distribution; normal approximation of binomial distributions; simple random sampling; point estimation; introduction to sampling distributions. Chapter 6 8 Sampling distribution of the sample mean; sampling distribution of the sample proportion; properties of point estimators; other sampling methods. Chapter 6 9 Interval estimation of a population proportion and estimation of a population mean, standard deviation known and unknown; determining sample size. Chapter 7 10 Developing null and alternative hypothesis; type I and type II errors; Tests about a population mean and proportion. Chapter 8 11 Tests about differences between the means of two populations, independent samples and matched samples. Tests about the differences in proportions. Chapter 9 12 Hypothesis tests about population variances and two population variances; Chapter 9 Goodness of fit test for multinomial populations; test of independence using contingency table. Chapter 11

3 13 The simple linear regression model; the least squares method. Chapter Chapter Test and/or review for Final Exam 15 Final Exam II. Course Goals*: A. Demonstrate descriptive methods of statistics, including frequency distribution, measures of central tendency, and measures of variation. VI.1-5 B. Examine bivariate data, cross-tabulations, sorting, graphics, and covariance and correlation. VI.1-5 C. Investigate probabilistic concepts. VI.1-5 D. Explore sampling and sampling distributions. VI.1-5 E. Master hypothesis testing. VI.1-5 F. Determine and interpret correlation and regression analysis. VI.1-5 G. Perform time series analysis. VI.1-5 H. Apply the most common probability distributions. VI.1-5 *Roman numerals after course objectives reference the general education goals. III. Expected Student Learning Outcomes *: Student will be able to: 1. Construct frequency distributions and frequency histograms. A, D 2. Calculate measures of central tendency. A 3. Calculate measures of dispersion. A 4. Construct scatter diagrams. B

4 5. Calculate correlation coefficients and establish the relative strength of the linear relationships between two variables. B, D, F 6. Construct time series charts and interpret the results. G 7. Calculate probabilities using both the classical and the empirical approaches. C 8. Calculate probabilities based on both the standardized and non-standard normal distributions. D, H 9. Perform hypothesis tests, including, but not restricted to, means testing (both large and small samples), and tests of independence and goodness of fit. D, E, H *Capital letters after Expected Student Learning Outcomes reference the course goals listed above. VI. Evaluation: A. Testing Procedures: Students are evaluated on the basis of tests, and at the teacher s discretion, quizzes, homework, computer projects, and case studies. A minimum of four major unit tests and a comprehensive departmental final will be given. All tests will be administered during scheduled lab times. B. Laboratory Expectations: At least half of all class meetings take place in the mathematics department computer lab. A minimum of ten of theses sessions will involve assignments to be turned in and graded, with the lab average making up a minimum of ten percent of the course grade. C. Field Work: None D. Other Evaluation Methods: None E. Grading Scale: A B B

6 Make-up Work: Instructor discretion about make-up tests and/or assignments. Cell Phones: Cell phones are to be either turned off or put on vibration mode while in class. Instructor discretion as to penalty.

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