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515—Statistical Methods I. (3) (Prereq: a grade of C or higher in MATH 111 or equivalent) Applications and principles of descriptive statistics, elementary probability, sampling distributions, estimation, and hypothesis testing. Inferences for means, variances, proportions, simple linear regression, and contingency tables. Statistical packages such as SAS.

Course Homepage: Spring 2011

Usually Offered: Fall, Spring, and Summer I Semesters

Learning Objectives: By the end of the term successful students should be able to do the following:

  • Understand and be able to correctly use basic statistical terms.
  • Recognize and evaluate variation in data using descriptive statistics, basic parameter estimation and hypothesis testing.
  • Compare data sets using descriptive statistics, parameter estimation, hypothesis testing and analysis of variance.
  • Recognize and evaluate relationships between two variables using simple linear regression.
  • Understand and be able to apply simple principles of probability.

    Current Textbook: Statistics, 11/E, by J.T. McClave and T. Sincich, Prentice Hall, 2008.
    Topics Covered
    Chapters
    		Time          
    Descriptive Statistics: graphical methods, measures of center and variability, use of SAS
    1-2
    		 1 weeks
    Basic Probability: basic rules of probability, probability distributions, binomial random variable and counting rules, normal distribution, normal approximation of the binomial (special case of the central limit theorem)
    3
    		 1 week
    Discrete Distributions
    4
    		 1.5 weeks
    Continuous Distributions
    6
    		 1.5 weeks
    Sampling Distributions: central limit theorem; t, chi-squared, and F distributions
    6
    		 2 weeks
    Estimation and Inference: confidence intervals and hypothesis tests for one and two means, variances, and proportions; p-value; power
    7-9
    		 4 weeks
    One-way ANOVA: the analysis of variance table and partitioning the sum of squares
    10.1-2
    		 1 week
    Simple Linear Regression: the least squares regression line, hypothesis testing and prediction, checking assumptions, the correlation coefficient
    11
    		 2 weeks
    Categorical Data Analysis: tests for independence, homogeneity, and goodness of fit
    13
    		 1 week

     

    The above textbook and course outline should correspond to the most recent offering of the course by the Statistics Department. Please check the current course homepage or with the instructor for the course regulations, expectations, and operating procedures.  

    Contact Faculty: Georgie Baker, Xiaoyan (Iris) Lin, David Hitchcock
    (Last Updated: August 17, 2011)

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