EXST 7003 - Statistical Inference I
Spring 2005

Course Description: EXST 7003 Statistical Inference I (4) F,S 3 hrs. lecture; 2 hrs. lab. Credit will be given for only one of the following: EXST 7003, 7004, 7005. Basic concepts of statistical models and sampling; descriptive and inferential methods; normal, t, chi-square, and F distributions; tests of hypothesis and estimation, analysis of variance, correlation, regression, analysis of categorical data; emphasis on social and behavioral sciences research problems; computer software applications.

Course Prerequisites: MATH 1021 or equivalent.

Course Objectives:  General objectives include the following:

  • Help student to recognize when statistical methods are necessary or may prove beneficial in decision making and scientific inquiry
  • Familiarize student with the terminology and mathematical language used to describe basic statistical techniques and models
  • Introduce student to several of the "well known" statistical methods
  • Provide the basic tools and building blocks for performing data analysis using analysis of variance and multiple regression methods
  • Provide a foundation for further study in statistics including both theory and methods
  • Demonstrate and provide hands-on practice with software that can be used to perform the analyses discussed throughout the course
  • Stimulate each student's general interest in and an appreciation for statistics and its application

Specifically, upon completion of the course, students should be able to:

  • Describe data using statistics both numerically and graphically
  • Understand the concept of a random variable; basic hypothesis testing concepts including p-values; elementary design and sampling concepts including randomization; and the use of models to explain phenomena observed in nature
  • Perform one and two-sample Z, t, and F tests for approximately normal random variables, and be able to interpret the test results
  • Perform analysis of two-way contingency tables to test for independence or homogeneity, as appropriate, and be able to interpret the test results
  • Perform simple and multiple linear regression analysis, interpret basic regression output, and perform basic model diagnostics
  • Perform basic analysis of variance (ANOVA) including simple diagnostics of and interpret the results from analyses of completely randomized designs and randomized complete block designs
  • Consult with a statistician at a basic level on designing experiments and analyzing data

Instructor: Dr. Barry Moser, 149A Ag. Administration Bldg, 578-8376, bmoser@lsu.edu.

Instructor Office Hours: LSU BlackBoard Discussion List (asynchronous), 9:35a-10:30a Mondays, 2:30p-3:30p Wednesdays, or by appointment (email me).

Required Text: Freund, R.J. and W.J. Wilson. 2003. Statistical Methods, second edition. Academic Press, San Diego, 673pp.

Assignments and Grading: Grades will be based upon 3 regular exams, 2 laboratory practica (midterm and final), a weekly lab grade based upon home-works, and a final exam. The final exam will be COMPREHENSIVE. Projects or outside work for additional credit are not permitted. You must take the exams and practica and turn in homework when scheduled unless you have received prior approval for alternative arrangements from the course or lab instructor, as appropriate. Practica will be taken in the laboratory at your regularly scheduled laboratory time. Dates below correspond to the week of each practicum. A grade of "incomplete" can not be given for unsatisfactory work or for failure to take exams or turn in homework when scheduled. Each exam, practicum, and the overall homework lab grade will be reported on a 100% basis. The Final Course Grade will then be computed by applying the percentages below to each of the items and summing them for the total score. Final letter grades will be assigned using the scale below. The instructor reserves the right to modify this scale by extending the lower limits on the minimum score required for a grade. 

        Instrument         Date     Percentage             Grade   Total Score
        ----------------   -------  ----------             -----   -----------
        Lab assignments    Weekly        6%                  A         >=90
        Exam 1             Feb 16       20%                  B        80-89
        Practicum 1        Mar 14        7%                  C        70-79
        Exam 2             Mar  9       20%                  D        60-69
        Exam 3             Apr  6       20%                  F          <60
        Practicum 2        May  2        7%
        Final              May  9       20%
        ----------------   -------  ----------
        Total                          100%

The Final Exam is scheduled for Monday, May 9, 2005 from 8:00p-10:00p in our regular classroom (classroom subject to change).


Topics: The topics and coverage will follow the text book using material through Chapter 8, and including material from Chapters 10 and 12. Text book chapters and/or sections [2nd edition]{revised edition when different from 2nd edition} are indicated within square brackets.

I. Introduction

·         Data, Distributions, Statistics, and Graphics[1.1-1.9]

II. Probability, Distributions, and Sampling

·         Concepts of Probability and Distributions[2.1-2.4]

·         Commonly Used Sampling Distributions[2.5-2.7]

III. Hypothesis Testing and Inference

·         Concept of Hypothesis Testing, Errors, and P-values[3.1-3.2]

·         Basics of Estimation[3.3]

·         Influence of Sample Size[3.4]

·         Importance of Model Assumptions[3.5-3.6]

IV. Single Population Inferences

·         Hypothesis Tests on a Population Mean[4.1-4.2]

·         Tests and Confidence Intervals for a Population Variance[4.4]

·         Review of Assumptions[4.5-4.6]

V. Two Population Inferences

·         Linear Combinations of Random Variables

·         The Difference Between Two Means Using Independent Samples[5.1-5.2]

·         The Ratio of Two Variances Using Independent Samples[5.3]

·         The Difference Between Two Means Using Paired Samples[5.4]

·         Model Assumptions[5.6-5.7]

VI. Inferences About Two or More Means

·         The Analysis of Variance (ANOVA)[6.1-6.2]

·         The Linear Model[6.3]

·         Model Assumptions[6.4]

·         Contrasts and Multiple Comparisons[6.5]

·         Random Effects Models[6.6]

·         Review[6.9]{6.10}

VII. Simple Linear Regression

·         The Regression Line[7.1-7.4]

·         Tests of Hypotheses Concerning the Line[7.5]

·         The Concept of Correlation[7.7]{7.6}

·         Basic Regression Diagnostics[7.8-7.9]{7.7-7.9}

VIII. Introduction to Multiple Linear Regression

·         The Multiple Regression Model[8.1]

·         The Concept of Partial Regression Coefficients[8.3]{8.3-8.4}

IX. Randomized Block Design Analysis

·         The Concept of Blocking in Design[10.2]

·         A Linear Model With a Fixed and a Random Effect[10.2]

X. Contingency Tables for Count Data

·         Hypothesis of Homogeneity of Proportions[5.5, 12.4]

·         Hypothesis of Marginal Homogeneity of Proportions[5.5]

·         Hypothesis of Independence for Two Categorical Factors[12.4]


 [2nd Edition]Freund, R. J. and W. J. Wilson. 2003. Statistical Methods, second edition. Academic Press, San Diego, CA, 673pp.

{Revised Edition}Freund, R. J. and W. J. Wilson. 1997. Statistical Methods, revised edition. Academic Press, San Diego, CA, 684pp.

 

Updated January 17, 2005