CRN: 72173

Credits : 4


This first course in statistics is designed to introduce students to basic statistical methods and techniques.  Students will learn how you organize and analysis data to support decision making.  Students will also learn how to be more discerning consumers of data presentations and analyses from other sources, such as government and company reports, published research findings, and popular media news coverage.  The course will feature an intensive lab experience using MS Excel.  Topics will include:


  • Descriptive Statistics:  Measures of central tendency (mean, median, mode), measures of dispersion (range, standard deviation, variance), graphical data presentation (charts, plots).
  • Probability and Common Distributions:  Definition of probability, basic laws of probability, random variables, discrete and continuous probability distributions (uniform,  binomial), the Normal distribution, Central Limit Theorem, standard error of the mean.
  • Inferential Statistics:  Sample versus population, sampling, hypothesis testing, significance level, Type I and Type II error, tests of distribution parameters, T-Test, confidence intervals.
  • Exploring Relationships among Variables:  Correlations, goodness of fit, linear regression analysis, explanatory versus predictive applications, nonlinear relationships.

Goals and Objectives

Students completing this course should be able to:


·        Create, read, and interpret graphs, charts, histograms, and diagrams.

·        Understand and use the basic measures of central tendency and dispersion.

·        Understand and use the language of probability and commonly used probability distributions.

·        Formulate and test hypotheses about population parameters in an appropriate manner.

·       Collect, organize, and represent data, and be able to recognize and describe relationships. 

·      Use MS Excel to analysis datasets in support of business decision making.  


  • MAT125  Technical Math I

    Course Materials

    Course Topics
    Introduction to Statistics  - Statistics and Critical Thinking -Types of Data; Sampling versus Population - Introduction to Excel Reading: Chapter 1 Homework: Review Ex: 1,3,5,7,9 (p.45-46) Excel Project: See assignment.Quiz 1 
    Summarizing and Graphing Data  • Frequency Distributions • Histograms • Use of Graphics to Inform and Misinform Reading: Chapter 2 Homework: Review Ex: 1,2,7 (p. 90-91) Excel Project: p. 92. Quiz 2 
    Basics of Descriptive Statistics  • Measures of Central Tendency • Measures of Dispersion • Measures of Relative Standing and Boxplots Reading: Chapter 3 Homework: Review Ex: 1,2,5,8 (p.148-149) Excel Project: p. 150.Quiz 3 
    Basic Concepts of Probability  • Addition and Multiplication Rules • Complements and Conditional Probability • Permutations and Combinations Reading: Chapter 4 Homework: Review Ex: 1 thru 10,13 (p.209-210) Excel Project: p. 213 Quiz 4 
    Discrete Probability Distributions  • Binomial Distributions • Parameters for Binomial Distributions • Discrete Probability Distributions Reading: Chapter 5 Homework: Review Ex: 1 thru 4,8,10 (p.259-260) Excel Project: p. 263 Quiz 5 
    Review for Midterm & Submit Overdue Work  Readings: None Homework: None Midterm Exam (Covers chp.1-5) 
    Normal Probability Distributions  • Sampling Distributions • Central Limit Theorem • Assessing Normality Reading: Chapter 6 Homework: Review Ex: 1,4,7 (p.342-343) Excel Project: None. Quiz 6 
    Estimating of Parameters and Sample Size  • Estimates of Confident Intervals • Estimates of Means • Estimates of Variance Reading: Chapter 7 Homework: Review Ex: 1,4,5,9 (p.401-402) Excel Project: None. Quiz 7 
    Inferential Statistics  • Hypothesis Testing • Type I and Type II Error • Applications and Examples Reading: Chapter 8 Homework: Review Ex: 2,3,6,8 (p.463-464) Excel Project: p. 467 Quiz 8 
    10  Inferences from Two Samples  • Two Means: Independent Samples • Two Means: Dependent Samples • Two Variances Reading: Chapter 9 Homework: Review Ex: 1,4,6,8 (p.522-523) Excel Project: p. 525 (Note: optional, extra credit project) Quiz 9 
    11  Correlations and Regression  • Correlation • Bivariate Regression • Multiple Regression Reading: Chapter 10 Homework: Review Ex: 1,3,5 (p.596-597) Excel Project: p.598-599 (Note: optional, extra credit project) Quiz 10 
    12  Review for Final Exam & Submit Overdue Work  Readings: None Homework: None Final Exam (Covers chp.6-10) 

    Proctor Information

    Register Now
    Seidenberg School of Computer Science and Information Systems
      Program Info | Admission | Registration | Go To Class | Home Copyright © 2000
    All rights reserved