Nov 21, 2024  
2023-2024 Undergraduate Academic Catalog-June Update 
    
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2023-2024 Undergraduate Academic Catalog-June Update [ARCHIVED CATALOG]

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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. 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.

  (prereq: MTH 1030  or MTH 1050  or MTH 1080  or equivalent) (quarter system prereq: MA 1204 or MA 125 or MA 120)

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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