MTH 155 Statistical Reasoning: Course Structure and Chapter Overview

MTH 155 Statistical Reasoning: Course Structure and Chapter Overview

Course Introduction

This pacing guide outlines the weekly coverage for a college-level statistics course, "Statistical Reasoning." The schedule is organized by chapters and sections, corresponding closely to standard statistics topics. Understanding the structure and sequence of these topics is essential for effective study and exam preparation.

Chapter and Topic Mapping

The course covers the following main topics, each corresponding to a chapter in a typical statistics textbook:

• Ch. 1 - Introduction to Statistics: Fundamental concepts, definitions, and the role of statistics in research and decision-making.

• Ch. 2 - Exploring Data with Tables and Graphs: Methods for organizing and visualizing data, including frequency tables and graphical representations.

• Ch. 3 - Describing, Exploring, and Comparing Data: Measures of central tendency, variability, and techniques for comparing datasets.

• Ch. 4 - Probability: Basic probability principles, rules, and applications.

• Ch. 5 - Discrete Probability Distributions: (Not explicitly listed, but may be included in probability sections.)

• Ch. 6 - Normal Probability Distributions: Properties of the normal distribution, z-scores, and applications.

• Ch. 7 - Estimating Parameters and Determining Sample Sizes: Confidence intervals and sample size calculations.

• Ch. 8 - Hypothesis Testing: Procedures for testing statistical hypotheses.

• Ch. 9 - Inferences from Two Samples: (Not explicitly listed, but may be covered in later sections.)

• Ch. 10 - Correlation and Regression: Relationships between variables, linear regression, and correlation coefficients.

• Ch. 11 - Goodness-of-Fit and Contingency Tables: Chi-square tests and analysis of categorical data.

• Ch. 12 - Analysis of Variance: (Not explicitly listed, but may be included in advanced topics or projects.)

Weekly Coverage Overview

The course is structured into 8-week blocks, with each week focusing on specific chapters and sections. Below is a summary table of the weekly coverage:

Week	Topics Covered	Key Activities
1	Ch. 1 (Intro, 1.1, 1.2, 1.3), Ch. 2.1	Syllabus Affidavit, Intro Discussion
2	Ch. 2.2, 2.3, 3.1	Regular instruction
3	Ch. 3.2, 3.3, 4.1	Test 1
4	Ch. 4.2, 4.3, 6.1, 6.2, 6.4	Regular instruction
5	Ch. 6.5, 7.1, 7.2	Test 2
6	Ch. 8.1, 8.2, 8.3, 10.1, 10.2	Regular instruction
7	Ch. 11.2	Test 3, Project
8	Project, Final Exam	Project due, Final Exam

Key Points for Study

• Sequential Learning: The course builds from basic concepts to advanced statistical methods. Early weeks focus on foundational knowledge, while later weeks introduce inferential statistics and multivariate analysis.

• Assessment Structure: Regular tests and a final exam ensure mastery of each topic. Projects may involve practical application of statistical reasoning.

• Flexibility: Students are encouraged to work ahead and manage their schedules around holidays and personal plans.

Example: Chapter Progression

For instance, after learning about data visualization in Chapter 2, students proceed to descriptive statistics in Chapter 3, followed by probability concepts in Chapter 4. This logical progression supports understanding of how data is collected, analyzed, and interpreted.

Additional info:

• Some chapters (e.g., Ch. 5, Ch. 9, Ch. 12) are not explicitly listed but may be integrated into other sections or projects.

• Section numbers (e.g., 1.1, 2.2) likely correspond to textbook subsections, providing detailed coverage of each topic.