BIOSTATISTICS
Academic year and teacher
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- Versione italiana
- Academic year
- 2022/2023
- Teacher
- GIORGIO BERTORELLE
- Credits
- 6
- Didactic period
- Primo Semestre
- SSD
- SECS-S/01
Training objectives
- Biostatistics is the first course for the degree in Biology where students will be exposed to biological data produced during an experiment or collected in the field. The major goal is of course to understand the importance of statistics for the study of biological processes. Basic concepts and techniques to quantify the uncertainty and to rigorously compare alternative hypotheses will be provided. One of the six credits of the course will we dedicated to teach how a simple multipurpose software package (EXCEL) can be used to organize and graphically represent a set of data, and to perform simple statistical analyses. Real biological examples will be used and discussed throughout all the course.
Knowledge acquired:
- Populations and samples
- Sampling errors and estimating with uncertainty
- Inferential statistics and hypothesis testing
- Basic tools for the analysis of categorical variables
- Normal distribution and basic tools for the analysis of numerical variables
Skills acquired:
- Use of indices to summarize data
- Use of graphs to display data
- Quantify the uncertainty associated with an estimate
- Select and perform basis statistical tests to compare null and alternative hypotheses
- Understand the limits and the assumptions of a test
- Understand the basic rules for planning an experiment or collect data in the field Prerequisites
- Basic knowledge in logics and mathematics, as acquired at the high school.
Course programme
- INTRODUCTORY LECTURES (15 hours
Statistics and samples
Populations and samples. Random sampling. Precision and accuracy. Types of variables. Experimental and observational studies. Confounding variables. Biology and the history of statistics.
Descriptive statistics: basics
Frequency distributions. Histograms and bar graphs. Visualizing two variables. Measures of location and spread.
Basic concepts of statistical inference
Sampling distribution. Estimating with uncertainty. Confidence intervals. Simple probability rules. Hypothesis testing. The p-value. Null distribution. Type I and type II errors. One sided and two sided tests. Statistical significance and biological importance. Pseudoreplication.
TESTS AND SAMPLING DESIGN (25 hours)
Analyzing proportions
Binomial distribution and binomial test. Errors in proportion estimates. The chi-square test statistic and its distribution. The chi-square test and its assumptions. Testing the Poisson distribution. Testing the association between categorical variables. The odds ratio.
Inference for a normally distributed variable
Normal distribution and standard normal distribution. Distribution of the sample mean and central limit theorem. The Student t statistic and its distribution. The t test for one sample, two samples, and two paired samples. One way ANOVA. Basic concepts of planned and unplanned comparison and multifactorial ANOVA. The assumptions of the t test and the ANOVA analysis. Correlation and regression.
Handling violations of assumptions
Data transformations. Nonparametric tests. Sign test. Mann-Whitney test. Assumptions of nonparametric tests.
Designing experiments and sampling strategies
How to reduce bias and sampling errors. Planning for precision and for power. The problem of multiple testing. Didactic methods
- 40 hours of theory and worked-out examples + 8 hours of EXCEL practice. For the latter set of hours, students can use their private laptop or tablet. The teacher will provide laptops if needed.
Learning assessment procedures
- Examination at the end of the course (one in January and one in February) will be written, with multiple choice questions and simple data sets to be analyzed with the appropriate statistical test. More specifically, the exam will include approximately 15 multiple choice questions, two/three short case studies, and two-three questions on Excel. Examination during the rest of the year (June, July, September) will be oral, and, as in the written exam, the teacher will verify both the comprehension of theoretical concepts and the ability to apply statistical tests.
Reference texts
- Analisi Statistica dei Dati Biologici. Michael C. Whitlock & Dolph Schluter. Second Italian Edition on the third American Edition, Zanichelli. 2022.
