Course Overview

This study guide summarizes the key elements of the MTH 104 - Elementary Statistics course at Daemen University, including course structure, learning objectives, grading, and a topical outline. The course provides an intuitive introduction to both descriptive and inferential statistics, emphasizing practical applications and the use of statistical software.

Course Description and Structure

• Course Title: Elementary Statistics (MTH 104)

• Credits: 3

• Delivery: 100% online, asynchronous via Blackboard

• Prerequisite: MTH 97 or equivalent competence

• Textbook: MyLab Statistics with Pearson eText (Elementary Statistics: Picturing the World, 8th Edition, Larson)

Learning Objectives

• LO.1: Use data collection and statistics to reach reasonable conclusions.

• LO.2: Recognize, examine, and interpret basic principles of describing and presenting data.

• LO.3: Compute and interpret empirical and theoretical probabilities.

• LO.4: Explain the role of probability in statistics.

• LO.5: Analyze and compare various sampling distributions for discrete and continuous random variables.

• LO.6: Describe and compute confidence intervals.

• LO.7: Perform hypothesis testing using statistical methods.

Course Topics and Schedule

The course is organized into modules that closely follow the standard sequence of topics in an introductory statistics course. Below is a summary of the main topics and their corresponding chapters:

Major Assignments and Grading

• Module Homework (36%): Online, auto-graded assignments for each module.

• Online Discussions (4%): Participation in discussion boards to enhance understanding.

• Midterm Exam (20%): Covers Chapters 1-3; multiple choice and short answer.

• Project (20%): Statistical comparison of two populations, including data collection, descriptive statistics, confidence intervals, and hypothesis testing.

• Final Exam (20%): Comprehensive, covering all course material.

Grading Scale

Project Overview: Comparing Populations

Project Steps

1. Formulate a Statistical Claim: State a hypothesis about the relationship between two population means.

2. Data Collection: Obtain random samples (n ≥ 30) from each population; describe sampling technique.

3. Descriptive Statistics: Calculate mean, median, mode, variance, and standard deviation for each sample.

4. Frequency Distributions & Histograms: Create and interpret histograms for each sample.

5. Confidence Intervals: Construct 90%, 95%, and 99% confidence intervals for each population mean.

   • General formula for confidence interval for mean (when population standard deviation is known):

   • When population standard deviation is unknown, use t-distribution:

6. Hypothesis Testing: Test the claim at 1%, 5%, and 10% significance levels (specify test type: z-test, t-test, one-tail, two-tail).

   • General form for hypothesis test for two means (independent samples):

   • (or , )

   • Test statistic (equal variances known):

   • Test statistic (variances unknown, use t-distribution):

7. Conclusion: Interpret results, discuss randomization, validity, possible reasons for results, and sources of error.

Academic and Professional Expectations

• High-quality, original work is required; academic integrity is strictly enforced.

• Assignments must be submitted on time; late work is penalized unless prior arrangements are made.

• Professional and respectful communication is expected in all course interactions.

Support and Resources

• Accessibility accommodations are available for students with documented disabilities.

• Technical support, research assistance, counseling, and academic services are provided by the university.

• Minimum technology requirements include a modern computer, reliable internet, and access to required software.

Summary of Main Statistics Topics Covered

• Ch. 1: Introduction to Statistics

• Ch. 2: Descriptive Statistics

• Ch. 3: Probability

• Ch. 4: Discrete Probability Distributions

• Ch. 5: Normal Probability Distributions

• Ch. 6: Confidence Intervals

• Ch. 7: Hypothesis Testing with One Sample

• Ch. 8: Hypothesis Testing with Two Samples

• Ch. 9: Correlation and Regression (implied by standard curriculum, though not explicitly listed in schedule)

• Ch. 10: Chi-Square Tests and the F-Distribution (implied by standard curriculum, though not explicitly listed in schedule)

Additional info: The syllabus provides a comprehensive overview of the course structure, expectations, and support resources, but does not include detailed content explanations or worked examples for each statistics topic. Students are expected to use the Pearson MyLab platform and the eText for in-depth study and practice problems.