| CODE | CPH1910 | ||||||||
| TITLE | Statistical Methods in Pharmacology | ||||||||
| UM LEVEL | 01 - Year 1 in Modular Undergraduate Course | ||||||||
| MQF LEVEL | 5 | ||||||||
| ECTS CREDITS | 2 | ||||||||
| DEPARTMENT | Clinical Pharmacology and Therapeutics | ||||||||
| DESCRIPTION | Statistics is a key and important tool in pharmacological research. It is of particular importance when attempting to determine whether the pharmacological effect of one drug is superior to another which clearly has implications for drug research and understanding mode of drug action in the basic, molecular and clinical settings. It is used to summarize (descriptive statistics) experimental data in terms of central tendency (mean or median) and variance (standard deviation, standard error of the mean, confidence interval or range). It also enables the researcher to conduct hypothesis testing in these scenarios. Therefore, it is essential for pharmacologists to have an understanding of the uses and abuses of statistical methods in basic, molecular and clinical pharmacology. In this study-unit, key statistical principles will be applied to the basic, molecular and clinical pharmacology setting. Focus will be placed, using practical examples in pharmacology of the importance of sampling, measures of central tendency, normal distribution, an understanding of confidence Intervals, hypothesis testing, T- tests and One - way Analysis of variance (ANOVA), Correlation and Chi-square test. Study-Unit Aims: This study-unit aims to provide a basic understanding of importance of appropriate statistical analysis in different spheres of pharmacology and thus avoiding common errors that can lead to false conclusions in the analysis of these results. Specifically it aims to: - Explore with examples the difference between populations, sample populations and samples and description statistics in pharmacology analysis - Highlight the difference between probability sampling procedures and non probability sampling procedures in various pharmacology scenarios. Study the different methods that exist in probability and non probability sampling procedures when analysing data obtained from pharmacology experiments. - Provide the equation of the normal distribution and understand how various areas within a normalized distribution can also represent probabilities of certain outcomes in clinical pharmacology. - Indicate how to estimate population characteristics based on sample data and create a confidence interval that properly estimate the true mean based on the sample means. - Explain the Student t-distribution and the t-tests associated with it in the analysis of pharmacology data. Learning Outcomes: 1. Knowledge & Understanding: By the end of the study-unit the student will be able to: - Provide holistically the importance of the various statistical techniques used in pharmacology. - Describe the main description statistics that consider the most important aspects being the center of that distribution (mode, median, and mean) and how the observations are dispersed within that distribution (range, variance, and standard deviation). Understand the difference between population and sample measures of central tendency in pharmacology. - Explain the appropriate use of statistics in analyzing pharmacological data - Describe how to use hypothesis testing to infer from a sample on whether to reject a statement about a population used in pharmacology analysis - Review Study the Student t-distribution and the t-tests associated with it. Moreover, the F-test of one-way analysis of variance will be studied in the context of being an extension from two-sample cases to k levels . 2. Skills: By the end of the study-unit the student will be able to: uate how a knowledge of statistics can be applied in basic, clinical and molecular pharmacology. - Apply their statistical knowledge in presenting and explaining results of the action of drugs in specific lab scenarios and populations. - Discuss the appropriate role of statistics in making recommendations about analysis of results in pharmacology experiments. - Explore potential statistically related issues in pharmacology papers. - Source and comprehend various statistical techniques in order to conduct research in the field of pharmacology. Main Text/s and any supplementary readings: Main Texts: - Chuang-Stein C, Kirby S (2021) Quantitative Decisions in Drug Development (Springer Series in Pharmaceutical Statistics). Springer 2nd edition. - Mitchell PJ (2022) Experimental Design and Statistical Analysis for Pharmacology and the Biomedical Sciences. Wiley-Blackwell; 1st edition - Rowe P. (2015) Essential Statistics for the Pharmaceutical Sciences. Wiley-Blackwell; 2nd edition Supplementary Readings: - De. Muth J E (2014), Basic Statistics and Pharmaceutical Statistical Applications - Third Edition, CRC Press. - Lew M, Good statistical practice in pharmacology Problem 1. Br J Pharmacol. 2007 Oct; 1Oct;152(3):295-83. - Lew M, Good statistical practice in pharmacology Problem 2. Br J Pharmacol. 2007 Oct; 152(3): 299鈥�303. |
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| STUDY-UNIT TYPE | Lecture and Independent Study | ||||||||
| METHOD OF ASSESSMENT |
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| LECTURER/S | Anthony Fenech (Co-ord.) Janet Mifsud |
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2025/6. It may be subject to change in subsequent years. |
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