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2024-2025 Undergraduate Academic Catalog-June 
    
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2024-2025 Undergraduate Academic Catalog-June
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MTH 2430 - Statistical Methods for Health Care

3 lecture hours 0 lab hours 3 credits
Course Description
This course discusses data analysis and the use of statistics in health care-related fields. Topics include collection, presentation, and measurement of qualitative, quantitative, continuous, and categorical data: feasibility, reliability, and validity of collection methods; sensitivity and specificity; predictive values, prevalence, and efficiency; comparison of sampling methods; and bias. Also discussed are methods of statistical analysis including one-parameter confidence intervals and hypothesis testing; analysis of variance, correlation, and regression. Finally, relative risk, odds ratio, and attributable risk are discussed. Microsoft Excel will be utilized throughout the course.
Prereq: MTH 1030  or MTH 1050  or MTH 1080  or equivalent (quarter system prereq: MA 1204 or MA 125 or MA 120)
Note: Students may receive credit for only one of MTH 2430, MTH 2450 , and MTH 2480 . This course is not available to students with credit for MTH 2410  or IND 2030 .
This course meets the following Raider Core CLO Requirement: Think Critically
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
  • Distinguish between various data types: quantitative, qualitative, continuous, and categorical
  • Differentiate between population and sample data
  • Represent data graphically using bar charts, pie charts, etc.
  • Calculate and interpret measures of central tendency and spread
  • Determine the feasibility, validity, and reliability of data collection methods
  • Calculate and interpret the sensitivity and specificity of collected data
  • Calculate and interpret predictive values, prevalence, and efficiency of collected data
  • Compare and contrast different sampling methods including nonprobability methods
  • Identify sampling error and bias
  • Calculate and interpret one-parameter mean and proportion confidence intervals
  • Perform and interpret one-parameter hypothesis testing of mean and proportions including P-value, type two error, power and determination of sample size
  • Perform and interpret the Chi-square test
  • Perform and interpret analysis of variance for two or more samples
  • Calculate and interpret correlation coefficients
  • Perform and interpret regression analysis
  • Compare and contrast relative risk, odds ratio, and attributable risk
  • Use Microsoft Excel to perform statistical analyses
Prerequisites by Topic
  • Evaluation of algebraic formulas
  • Familiarity with two-dimensional graphs
Course Topics
  • Collection and presentation of data
  • Measurement of central tendency and spread
  • Evaluation of sampling methods and collected data
  • Confidence intervals for one mean and one proportion
  • Hypothesis testing for one mean and one proportion
  • Chi-square test
  • Analysis of variance (ANOVA)
  • Regression and correlation
  • Relative risk, odds ratio, attributable risk
Coordinator
Dr. Lesya Chorna


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