JORDAN   UNIVERSITY OF SCIENCE AND TECHNOLOGY

Faculty of Medicine - DEPT. of Public Health.

 

(PH 311) -  2 Credit Hours

Biostatistics for Health Sciences Students

                                  

1. COURSE DESCRIPTION

The course focuses on descriptive and inferential statistics as applied to medical practice.

The course starts with descriptive measures and probability concepts. Conditional probability and Bayes theory are given due emphasis to compute validity indicators for clinical and laboratory tests, i.e. sensitivity, specificity and predictive values for single and multiple tests.

The students are trained to draw statistical inferences by two main methods these are: Estimation and Hypothesis testing. Chi-square variants are discussed with relevant clinical examples.

Students are trained to use computer software in solving assigned exercises. The standard text book used in this course is W. Daniel Biostatistics. This text book uses Mini tab soft ware computer program. The students are provided with necessary     Mini tab software at the beginning of the course to be used during the course in solving practical exercises and in data analysis.

 

2. GENERAL OBJECTIVES

1)      organize, summarize and present data related to health sciences.

     2)  Define representative and appropriate sample from a certain population using the   appropriate sampling technique.

    3)  Estimate population parameters (means and proportions) with high reliability based on the information contained in the sample.

    4)  Test any hypothesis about the population parameters.

    5)  Reach decisions about large body of data by examining only a small part of the data.

6)    Draw scientific conclusions from data.

 

4. EVALUATION

        First Exam  =  30%

        Second Exam  =  30%

   Final Exam  =  40%

 

5. RECOMMENDED TEXT BOOKS

Wayne Daniel, Biostatistics: A Foundation for Analysis in the Health Sciences, Eighth Edition, 2005, John Wiley, Newyork

 

 

LEARNING TOPICS

 

WEEK                       TOPIC                                .

 

 1                                     Definitions of terms

 

 2                                    Descriptive statistics:   Frequency distribution

                                                                             Measures of central tendency

 3                                    Descriptive statistics:  Measures of variability

 

 4                                    Probability concepts

 

 5                                    Bayes Theorem:       Validity indicators

                                                                     Positive and negative predictive values

 

 6                                          First term exam.

 

 7                                    Probability distribution: Binomial distribution

                                                                            Normal, standard normal distribution

 

 8                                    Sampling distributions

 

 9                                    Estimation of population parameters (mean, proportion)

 

 10                                  Estimation - difference between two means, two proportions 

 

 11                                        Second term exam.

 

 12                                  Hypothesis testing: Introduction

 

 13                                   Hypothesis testing: One-sample t test

                                        Hypothesis testing:  Proportion test (Z test)

 

 14                                   Hypothesis testing: Difference between two means t-test

                                       Hypothesis testing: Paired t-test

                                       Hypothesis testing: Difference between two proportions

 

 15                                  Chi-square tests

                           Chi-square test:  Relative risk, Odds ratio