الاحصاء الحيوي

Department: Family and community medicine                                            tutorial:                                                                           

Learning objectives:

By the end of this lecture, students should be able to:

1. Identify rational of statistics in medical practice.

2. Recognize the relation between statistics, epidemiology and computer science ,

    complementary discipline in medical practice .  

3. Define biostatistics with its types and the difference between them.

4. define a variable and identify different types of variables and scales of measurement

5. Differentiate between, a variable, data and information.

Detailed content:

Definitions:

- Variables, data, information ,statistics; both descriptive & analytic. 

- Types of data; quantitative & qualitative .

Methods:  Lecture

Readings:

We don't closely follow specific text for this course. We will provide lecture notes through out the course. however, if u wish to consult a book, we suggest the following boxes:

1. "An introduction to Statistical Methods & Data Analysis." R.Lyman Ott & Michael Longnechar, Duxbury Press, 5^th edition , 2001

2."Statistics: The Art and Science of learning from data". Agresti and Franklin

3."Introduction to the practice of statistics, 5^{th edition}, Moore & Mcabe.

4. "Text book: Statistical Concepts & Methods". Bhattacharyya and Johson (wiley)

Department: Family and community medicine                                          tutorial:                                                                   

Learning objectives:

By the end of this lecture, students should be able to:

1. Define population and sample

Sources of data collection -2. Identify the different :

                                        - Data forms , coding table and coding dictionary

                                        - Data reduction

3. Describe the basic concepts and different methods of tabular presentation of data

4. Describe the basic concepts and different methods of graphical presentation of data.

Detailed content:

1. Collection of data: sources, whole population studies, sampling.

2. Describing data resulting from a categorical variable: Tally and frequency tables, bar graph, bie chart.

3. Describing data resulting from two  categorical variables: contingency tables, marginal percentages, conditional percentages, side by side bar graphs

4. Summary characteristics and features of measurements data: Distribution shape, center, variability.

5. Graphical and numerical summaries for measurements data:

 - Univariate analysis: line plots, dot plots, histograms, stem leaf plots, box plots, line graphs, time plot.

 - Brivariate analysis: Use of scatter plots, correlation, fitting a line.

Methods: Lecture/ Computer lab.

Readings:

We don't closely follow specific text for this course. We will provide lecture notes through out the course. however, if you wish to consult a book, we suggest the following boxes:

1. "An introduction to Statistical Methods & Data Analysis." R.Lyman Ott & Michael Longnechar, Duxbury Press, 5^th edition , 2001

2."Statistics: The Art and Science of learning from data". Agresti and Franklin

3."Introduction to the practice of statistics, 5^{th edition}, Moore & Mcabe.

4. "Text book: Statistical Concepts & Methods". Bhattacharyya and Johnson (wiley).

Teaching location:

Learning objectives:

By the end of this lecture, students should be able to:

1. Define and determine the various measures of central tendency

2. Define and determine the various measures of dispersion

3. Explain why the mean ± 2 standard deviations is often used to establish the "normal range" and what practical difficulties might be encountered using this procedure in clinical practice.

Detailed content:

1. Descriptive statistics for numerical data: measures of central tendency (mean, median, mode).

2. Descriptive statistics for nominal data: proportions & percentages.

3. Measures of variability: the range, the variance, the standard deviation and coefficient of variation.

Methods: Lecture/ Computer lab.

Readings:

We don't closely follow specific text for this course. We will provide lecture notes through out the course. however, if you wish to consult a book, we suggest the following boxes:

1. "An introduction to Statistical Methods & Data Analysis." R.Lyman Ott & Michael Longnechar, Duxbury Press, 5^th edition , 2001

2."Statistics: The Art and Science of learning from data". Agresti and Franklin

3."Introduction to the practice of statistics, 5^{th edition}, Moore & McCabe.

4. "Text book: Statistical Concepts & Methods". Bhattacharyya and Johnson (Wiley).

Department: Family and community medicine                                           tutorial:

Teaching location:

Learning objectives:

By the end of this lecture, students should be able to:

1. Define the normal distribution and describe its characteristics

2. Contrast the features of a normal distribution to those of skewed distribution or kertotic one

3. Define the standard normal distribution and how to use it to estimate the standard value (z- value).

4. Define and estimate the standard error and to know its applications in the clinical practical field. 

Detailed content:

1- Normal distribution curve and percentiles.

2- Skew ness and kurtosis.

3- z-score

4- Standard error of the mean (SEM).

5- Standard error of proportion

Methods: Lecture/ Computer lab.

Readings:

We don't closely follow specific text for this course. We will provide lecture notes through out the course. however, if  you wish to consult a book, we suggest the following boxes:

1. "An introduction to Statistical Methods & Data Analysis." R.Lyman Ott & Michael Longnechar, Duxbury Press, 5^th edition , 2001

2."Statistics: The Art and Science of learning from data". Agresti and Franklin

3."Introduction to the practice of statistics, 5^{th edition}, Moore & Mcabe.

4. "Text book: Statistical Concepts & Methods". Bhattacharyya and Johson (wiley) 

Department: Family and community medicine                                   tutorial:                                                                  

Teaching location:

Learning objectives:

By the end of this lecture, students should be able to:

1.Use the standard error to estimate the different confidence limits( range of probability):

                      - Estimate confidence interval for a mean

                      - Estimate confidence interval for a proportion

2. Interpret statements containing confidence limits.

3. Make defensible inferences about samples and populations:

                      - Estimate a single population mean μ when the standard deviation σ is

                        Known.

                      - Estimate a single population proportion.                       

Detailed content:

       Point estimate , interval estimate, the upper and lower confidence limits ( range of probability ) i.e. confidence intervals; 90% C.I, 95% C.I, 99% C.I .

Methods: Lecture.

Readings:

We don't closely follow specific text for this course. We will provide lecture notes through out the course. however, if u wish to consult a book, we suggest the following boxes:

1. "An introduction to Statistical Methods & Data Analysis.". R.Lyman Ott & Michael Longnechar, Duxbury Press, 5^th edition , 2001

2."Statistics: The Art and Science of learning from data". Agresti and Franklin

3."Introduction to the practice of statistics, 5^th  edition ,Moore & Mcabe.

4. "Text book: Statistical Concepts & Methods". Bhattacharyya and Johson (wiley) 

Department: Family and community medicine                                 Tutorial:                                                       

Teaching location:

Learning objectives:

By the end of this lecture, students should be able to:

1. Recognize the difference between population distribution and sampling distribution.

2. Outline basic concepts of hypothesis testing.

3. Recognize the types of question-problems (description, estimation, comparison and relation).

4. Interpret statements of statistical significance with regard to comparisons of means and frequencies, and explain what is meant by a statement such as "p<0.05".

5. Distinguish between the statistical significance of a result and its importance in clinical application.

Detailed content:

Null hypothesis, Alternative hypothesis, α error (type I error), β error (type II error), confidence level, power of the test, p-value.

Methods: Lecture.

Readings:

We don't closely follow specific text for this course. We will provide lecture notes through out the course. however, if you wish to consult a book, we suggest the following boxes:

1. "An introduction to Statistical Methods & Data Analysis". R.Lyman Ott & Michael Longnechar, Duxbury Press, 5^th edition , 2001

2."Statistics: The Art and Science of learning from data". Agresti and Franklin

3."Introduction to the practice of statistics". 5^{th edition}, Moore & Mcabe.

4. "Text book: Statistical Concepts & Methods". Bhattacharyya and Johson (wiley)

Department: Family and community medicine                              Tutorial:                                                            

Teaching location:

Learning objectives:

By the end of this lecture, students should be able to:

1. Describe meaning and uses of hypothesis testing of arithmetic means.

2. Recognize and calculate the statistical test appropriate for comparison between one

    sample mean & a population mean.

3. Recognize and calculate the statistical test appropriate for comparison between two

    independent means.

4. Recognize and calculate the statistical test appropriate for comparison between two

    means in a paired sample.

5. Recognize the statistical test appropriate for comparison between more than two

    independent means.

Detailed content:

One sample "t" test, Student "t" test, Paired "t" test, ANOVA test.

Methods: Lecture/ Computer lab.

Readings:

We don't closely follow specific text for this course. We will provide lecture notes through out the course. however, if you wish to consult a book, we suggest the following boxes:

1. "An introduction to Statistical Methods & Data Analysis." R.Lyman Ott & Michael Longnechar, Duxbury Press, 5^th edition , 2001

2."Statistics: The Art and Science of learning from data". Agresti and Franklin

3."Introduction to the practice of statistics, 5^{th edition}, Moore & Mcabe.

4. "Text book: Statistical Concepts & Methods". Bhattacharyya and Johson (wiley) .

Department: Family and community medicine                                 Tutorial:                                                            

Teaching location:

Learning objectives:

By the end of this lecture, students should be able to:

1. Recognize and calculate the statistical test appropriate for comparison between two independent proportions.
2. Recognize and calculate the statistical test appropriate for comparison between more than two independent proportions
3. Recognize and calculate the statistical test appropriate for comparison between two proportions in a paired sample .

Detailed content:

"z" test, x² text, Mc Nemar test, Fisher exact test.

Methods: Lecture/ Computer lab.

Readings:

We don't closely follow specific text for this course. We will provide lecture notes through out the course. however, if you wish to consult a book, we suggest the following boxes:

1. "An introduction to Statistical Methods & Data Analysis." R.Lyman Ott & Michael Longnechar, Duxbury Press, 5^th edition , 2001

2."Statistics: The Art and Science of learning from data". Agresti and Franklin

3."Introduction to the practice of statistics, 5^{th edition}, Moore & Mcabe.

4. "Text book: Statistical Concepts & Methods". Bhattacharyya and Johson (wiley) .

Lecture#9

Sampling techniques : probability & non probability

Department: Family and community medicine                            Tutorial:                                                            

Teaching location:

Learning objectives:

By the end of this lecture, students should be able to:

1. List at least four advantages of sampling.

2. Describe different sampling techniques.

3. Explain sampling bias and describe how random sampling operates to avoid bias in the of data collection.

4. List types and methods of probability sampling.

5. List types and methods of non- probability sampling.

6. Distinguish between standard deviation and standard error, and give one example of the use of each.

Detailed content:

Steps in sample selection: sampling frame, sample size, randomization.

Simple random sample, systemic random sample, stratified random sample, cluster sample, multistage random sample.

Convenience sample, Consecutive sample, Judgmental sample.

Methods: Lecture/ Computer lab.

Readings:

We don't closely follow specific text for this course. We will provide lecture notes through out the course. however, if u wish to consult a book, we suggest the following boxes:

1. "An introduction to Statistical Methods & Data Analysis." R.Lyman Ott & Michael Longnechar, Duxbury Press, 5^th edition , 2001

2."Statistics: The Art and Science of learning from data". Agresti and Franklin

3."Introduction to the practice of statistics, 5^{th edition}, Moore & Mcabe.

4. "Text book: Statistical Concepts & Methods". Bhattacharyya and Johson (wiley).

Lecture#10

Correlation:

Department: Family and community medicine                                   Tutorial:                                                              

Teaching location:

Learning objectives:

By the end of this lecture, students should be able to:

1. Recognize the question problem of correlation between two interdependent variables.
2. Interpret the relationship between two variables as displayed on a scatter gram.
3. Distinguish between positive, negative and zero correlation.
4. Recognize and interpret Pearson's correlation for two variables of interval.
5. Detect the significance of correlation between two interdependent variables.

Detailed content:

Scatter gram, correlation coefficient "r", and t-test of the "r".

Readings:

We don't closely follow specific text for this course. We will provide lecture notes through out the course. however, if you wish to consult a book, we suggest the following boxes:

1. "An introduction to Statistical Methods & Data Analysis." R.Lyman Ott & Michael Longnechar, Duxbury Press, 5^th edition , 2001

2."Statistics: The Art and Science of learning from data". Agresti and Franklin

3."Introduction to the practice of statistics, 5^{th edition}, Moore & Mcabe.

4. "Text book: Statistical Concepts & Methods". Bhattacharyya and Johson (wiley)  .

Methods: Lecture/ Computer lab.

Lecture#11

Regression analysis:

Department: Family and community medicine                                   Tutorial:                                                            

Teaching location:

Learning objectives:

By the end of this lecture, students should be able to:

1.      Develop a predictive model to predict a dependent variable value given a specific level of an independent variable which is correlated to it.

2.      Explain the information provided by a regression equation.

3.      Distinguish between a simple regression equation and a multiple regression one.

Detailed content:

1. The best fitted line in a scatter plot, its slope and intercept.

2. Residual error

3. Linear regression equation

4. Regression coefficient.

5. Coefficient of determination.

Methods: Lecture/ Computer lab.

-Objectives of the lectures

 Biostatistics:

      1- Develop the concept of critical interpretation of data.

      2- Enable future doctors to use statistical principles to improve

           their professional work.

      3- Help future researchers in the medical field to make optimum use

          of their resources to reach valid research conclusions.

      4- Help students to understand medical literatures and make critical

Learning Resources

Textbooks:

     Statistics In Medicine.

Thedore Colton,Sc.D.

N.B.  Some lectures will have handouts to clear and simplify what is become in these textbooks. However, the department have elaborated these handouts to the point where they represent a data textual description of the material within the course curriculum  and so can be used as the primary reference in lieu of the textbook e.g. biostatistics lectures.

Example of Questions with model answer

Select the best answer from the following multiple answers: Two tests (ELIZA & PCR) were conducted for diagnosis of HBV among 600 persons. Results showed that a total of 300 persons were + ve by ELIZA screening test, and 50 % of these screening test + ve were also positive by PCR confirmatory test. On the other hand, 90 % of those were screening test –ve are also –ve by PCR diagnostic test.

Answer the following questions: (you can use approximation)

-The sensitivity of ELIZA test was:

a.       30 %.

b.      50 %.

c.      64 %.

d.      83 %.√

e.       90 %.

-The specificity of ELIZA test was:

a.       30 %.

b.      50 %.

c.      64 %.√

d.      80%.

e.       90 %.

-The positive value of predicted test (positive predicted test) of ELIZA was:

a.       30 %.

b.      50 %. √

c.      64 %.

d.      80%.

e.       90 %.