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Statistics I (MATH 250 BDE) Syllabus and Study Guide

Study Guide - Smart Notes

Tailored notes based on your materials, expanded with key definitions, examples, and context.

Course Overview

Introduction to Statistics I

This course provides a comprehensive introduction to descriptive and inferential statistics, focusing on the collection, analysis, and interpretation of data. Students will learn to apply statistical methods to real-world problems, develop quantitative reasoning skills, and communicate statistical findings effectively.

  • Credit Hours: 3.00

  • Location: Online

  • Prerequisites: Grade of C or higher in MATH 104, or qualifying scores on standardized tests or placement exams.

Required Materials

Textbook and Courseware

  • MyLab Math for Essential Statistics by Gould (Pearson, 3rd Edition)

  • Courseware access required for assignments and homework.

Textbooks may be provided as eTexts or physical copies. Students are responsible for returning physical materials if the course is dropped or canceled.

Technology Requirements

Online Learning Tools

  • A computer with reliable Internet access

  • A web browser

  • Acrobat Reader

  • Microsoft Office or equivalent word processor

  • Webcam and microphone for proctored exams

Course Learning Outcomes

Key Competencies

  • Construct and interpret graphical displays of qualitative and quantitative data.

  • Describe distributions of quantitative data in terms of shape, center, and spread.

  • Use appropriate methods to explore and describe relationships between two variables.

  • Compute and interpret probabilities and conditional probabilities; use probabilities to determine if events are independent.

  • Compute and interpret point estimates and interval estimates for means and proportions.

  • Test hypotheses for a single mean or proportion using p-values and interpret results.

Grading Scale

Letter Grades and Percentages

Grade

Points

Percent

A

900 - 1000

90 - 100%

B

800 - 899

80 - 89%

C

700 - 799

70 - 79%

D

600 - 699

60 - 69%

F

0 - 599

0 - 59%

Grading Weights

Assignment Categories

Category

Points

Percent

Discussions (7)

130

13%

Dropbox Assignments (3)

150

15%

Quizzes (7)

280

28%

MyLabs Homework (7)

160

16%

Final Project

250

25%

QLRA

30

3%

Total

1000

100%

Schedule of Due Dates

Weekly Assignments

  • Discussions: Weekly, due Thursday/Sunday

  • MyLabs Homework: Weekly, due Sunday

  • Quizzes: Weekly, due Sunday

  • Dropbox Assignments: Weeks 2, 4, 6, due Sunday

  • Final Project: Week 8, due Thursday

  • QLRA: Week 8, due Saturday

Assignment Overview

Instructional Materials

  • Weekly readings from the textbook and courseware

  • Additional instructional materials provided in the course content area

Discussions

  • Seven graded discussions, focusing on key concepts and practical applications

  • Initial post required by Thursday; responses by Sunday

  • APA style recommended for references

Dropbox Assignments

  • Three assignments emphasizing technology and application of statistical concepts

  • Each worth 50 points, due Sunday of assigned week

MyLabs Homework

  • Weekly assignments aligned with textbook readings

  • Grades transferred to D2L gradebook

  • Total of 160 points

Quizzes

  • Weekly quizzes (multiple-choice and short answer)

  • Each quiz worth 40 points; best attempt recorded

  • Up to 5 attempts per quiz allowed

Final Project

  • Comprehensive paper demonstrating statistical concepts and communication skills

  • Includes survey design, data analysis, and visual presentation

  • Worth 250 points, due Week 8

QLRA (Quantitative Literacy and Reasoning Assessment)

  • Assesses quantitative skills and reasoning

  • Includes multiple-choice problems and general questions

  • Worth 30 points, taken in D2L during Week 8

College Policies and Procedures

Key Policies

  • Graduate and Undergraduate Grading Policy

  • Registration, Withdrawal, and Drop Policies

  • Alcohol and Other Drugs Policy

  • Family Educational Rights and Privacy Act (FERPA)

Academic Integrity and Plagiarism

  • All work must be original and properly cited

  • Plagiarism and academic misconduct are strictly prohibited

  • Papers are subject to plagiarism detection software

Additional Info

  • Students are expected to participate actively and meet all deadlines

  • Technical support and tutoring services are available

  • Accessibility accommodations can be arranged through Student Access Resources

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