ZMATH 115 - Introduction to Statistical Methods

Note: there is no credit by exam. Please remove this from the formerly approved (Nov. 2023) course description.  (Fall, Spring & Summer Only) Four hours lecture each week. Four Credits. Four billable hours.


GENERAL EDUCATION. Category: Mathematics

Pre-requisite(s): see "Pre- / Co-requisites"
Co-requisite(s): see "Pre- / Co-requisites"
Pre-/Co-requisite(s): Eligibility for ENGL 101 and satisfactory placement measure or completion of MAT 095 with a minimum grade of C or better, or a co-requisite of MAT 015. 

Advanced Placement Exam-'Statistics with a score of 3' accepted. (MATH coursework is recommended to be completed within 2 years. High school GPA placement is accepted within 5 years). 

Other Placement Measures (minimum scores provided): 

HS GPA: 2.6

ALEKS PPL: 30 (no change)

SAT: 530 (no change)

ACT: 21 (no change)

AP Test Score of 3: Stat, Precalc, Calc AB, or Calc BC 

GED Math Reasoning: 165 (no change)

Any college-level MATH course with a grade of D or higher (no change)

Associate's or Bachelor's Degree from Accredited College (no change)

Course Topics:
No change:

1. Introduction to Statistical Concepts:
   • Notation, symbols, and terminology in statistics
   • Types of data and measurement scales
2. Data Summarization and Visualization:
   • Measures of central tendency (mean, median, mode)
   • Measures of variability (range, variance, standard deviation)
   • Data visualization techniques (histograms, box plots, scatter plots)
3. Probability:
   • Probability distributions (Binomial, Normal)
   • Probability calculations for discrete and continuous random variables
4. Central Limit Theorem:
   • Understanding and applying the Central Limit Theorem
   • Sampling distribution of the sample mean
5. Confidence Intervals:
   • Construction and interpretation of confidence intervals
   • Confidence intervals for population means and proportions
   • Confidence intervals for differences between means and proportions
   • Confidence intervals for linear correlations
6. Hypothesis Testing:
   • Hypothesis testing fundamentals
   • One-sample and two-sample hypothesis tests
   • Tests for population means and proportions
   • Tests for linear correlations
7. Chi-Squared Tests:
   • Chi-squared test for independence
   • Chi-squared goodness-of-fit test
8. Technology in Statistical Analysis:
   • Utilizing statistical software

1. Articulate statistical concepts using appropriate symbols, notation, and vocabulary, ensuring accurate and clear communication of ideas and results. (GE1)
2. Summarize data using a variety of methods. (GE2, GE5)
3. Identify probabilities for both discrete and continuous random variables. (GE2, GE3, GE5)
4. Interpret the Central Limit Theorem when dealing with sample means, allowing for robust statistical inference. (GE1, GE2, GE3, GE5)
5. Construct confidence intervals using sample data to estimate population parameters and linear correlations. (GE1, GE2, GE3, GE5)
6. Conduct hypothesis tests to make informed inferences about population parameters and linear correlations based on sample data, providing a solid foundation for decision-making. (GE1, GE2, GE3, GE5)
7. Employ chi-squared distributions for hypothesis testing and analysis in various statistical scenarios. (GE1, GE2, GE3, GE5)
8. Utilize modern technology and statistical software tools effectively to accurately solve complex statistical problems and enhance decision-making. (GE5)