# 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 **

** **

** **