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MATH 270 Syllabus

Statistical Methods I

Revised: April 11, 2022

Course Description

This course focuses on inferential statistics including confidence intervals and hypothesis tests. Sampling distributions for sample proportions and means. Confidence intervals and hypothesis tests for one and two population proportions, means and standard deviations. Chi-square tests for goodness-of-fit and two-way tables. One-way analysis of variance and multiple comparisons. Simple linear and multiple linear regression.

Prerequisite: MATH 146 or 153 or placement.
Three semester hours.

Student Learning Objectives

  1. Describe the concepts of population and sample, and some of the basic descriptive measures associated with them.
  2. Explain graphical methods for data presentation.
  3. Interpret estimation and hypothesis testing procedures applied to population means, proportions and variances.
  4. Compare multiple means, proportions and variances using appropriate statistical analyses.
  5. Synthesize the ideas of correlation and regression.
  6. Model univariate and multivariate data using linear models.
  7. Determine the appropriate statistical method to use given a set of data.

Text

Michael Sullivan, III. Statistics: Informed Decisions Using Data, Sixth Edition. (Pearson), 2021.

Grading Procedure

Grading procedures and factors influencing course grade are left to the discretion of individual instructors, subject to general university policy.

Attendance Policy

Attendance policy is left to the discretion of individual instructors, subject to general university policy.

Course Outline

  • Chapter 7: The Normal Probability Distribution (0.5 week)
    • Properties of the Normal Distribution.
    • Applications of the Normal Distribution.
    • Assessing Normality.
  • Chapter 8: Sampling Distributions (1 week)
    • Distribution of the Sample Mean.
    • Distribution of the Sample Proportion.
  • Chapter 9: Estimating the Value of a Parameter (2 weeks)
    • Estimating a Population Proportion.
    • Estimating a Population Mean.
    • Estimating a Population Standard Deviation.
  • Chapter 10: Hypothesis Tests Regarding a Parameter (2.5 weeks)
    • The Language of Hypothesis Testing.
    • Hypothesis Tests of a Population Proportion.
    • Hypothesis Tests for a Population Mean.
    • Hypothesis Tests for a Population Standard Deviation.
  • Chapter 11: Inference on Two Population Parameters (2 weeks)
    • Inference about Two Population Proportions.
    • Inference About Two Means: Dependent Samples.
    • Inference about Two Means: Independent Samples.
    • Inference about Two Population Standard Deviations.
  • Chapter 12: Inference on Categorical Data. (1 week)
    • Goodness-of-Fit Test.
    • Tests of Independence and the Homogeneity of Proportions.
  • Chapter 13: Comparing Three or Means. (1 week)
    • Comparing Three or Means (One-Way Analysis of Variance).
    • Post Hoc Tests on One-Way Analysis of Variance
  • Chapter 14: Inference of the Least-Squares Regression Model and Multiple Regression. (2 weeks)
    • Testing the Significance of the Least-Squares Regression Model.
    • Introduction to Multiple Regression.