Course

Course Summary
Credit Type:
Course
ACE ID:
OOSL-0070
Organization's ID:
MAT202
Organization:
Location:
Online
Length:
14 weeks (75 hours)
Dates Offered:
Credit Recommendation & Competencies
Level Credits (SH) Subject
Lower-Division Baccalaureate 3 Introduction to Statistics
Description

Objective:

Th course objective is to introduce the basic ideas of statistics, making it perfect for students who want to understand how data influences decision-making in a variety of domains. It goes over the fundamentals of probability, data sampling concepts, and tabular and graphical data presentation techniques. Students will study statistical estimate methods, random variables, and important ideas in hypothesis testing. Additionally, the course introduces analysis of variance (ANOVA) and explores bivariate correlations. With a balanced focus on theory and application, this course lays the groundwork for advanced studies in statistics and data analysis.

Learning Outcomes:

  • Understand fundamental statistical terms and concepts, explain different sampling methods, and distinguish between various types of study designs
  • Construct various charts and graphs to display numerical and categorical data effectively, and calculate and interpret measures of center and spread within the context of diverse datasets
  • Understand basic concepts, types, and rules of probability theory, analyze multi-event scenarios to assess outcome likelihood, and calculate conditional probabilities using appropriate formulas and rules
  • Compute probabilities for both discrete and continuous random variables, and demonstrate proficiency in identifying and calculating probabilities using the normal distribution
  • Understand the role of sampling distribution and construct and interpret confidence intervals in estimating population parameters
  • Formulate hypotheses and conduct hypothesis tests for one-sample and two-sample scenarios
  • Perform Chi-Square tests, compute correlation coefficients, and apply linear regression for predictive modeling, drawing meaningful conclusions from the results
  • Apply analysis of variance (ANOVA) to compare means across multiple groups
  • Analyze real-world data through case studies and practice sets to develop practical skills in statistical reasoning and problem-solving

General Topics:

  • Foundations of Statistical Analysis
  • Descriptive Statistics
  • Probability
  • Random Variables
  • Statistical Estimation
  • Hypothesis Testing
  • Bivariate Relationships
  • Analysis of Variance
  • Final Exam
  • Conclusion
Instruction & Assessment

Instructional Strategies:

  • Audio Visual Materials
  • Computer Based Training
  • Laboratory
  • Practical Exercises

Methods of Assessment:

  • Examinations
  • Quizzes

Minimum Passing Score:

70%
Supplemental Materials

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