Biostatistics 1

(BEGINNER COURSE)

Looking to advance your data analysis skills? Our Biostatistics 1 Course is perfect for healthcare professionals, biomedical researchers, and scientists. You’ll gain a solid foundation in statistical methods, learn to interpret data, and apply these techniques using SAS® Studio. With flexible online learning and personalized support, you can master key skills at your own pace and work with real-world data.

 

Upon successful completion of the course, participants will be equipped to independently formulate statistical hypotheses, conduct exploratory data analysis, and create tables and graphs using statistical software. They will also learn to select the appropriate statistical test and correctly interpret the analysis results, thereby ensuring a thorough understanding of statistical concepts.

Course Program

 

1. Introduction to Software
a. Data import
b. Data quality control
c. Data preparation for analysis
d. Steps for conducting descriptive analyses
e. Steps for creating graphical representations
f. Steps for conducting inferential analyses
g. Creating tables and graphs in a report-friendly format

2. Descriptive Statistics
a. Types of data
b. Parameters and statistics of interest for different types of data
c. Graphical representations for various types of data
d. Normal distribution and how we describe it
e. Deviations from normal distribution
f. Types of research
g. Population and sample
h. Randomization

3. Inferential Statistics
a. Sampling distribution and the central limit theorem
b. Point and interval estimates (confidence intervals for means and proportions)
c. Data analysis process
d. Determining sample size
e. Hypothesis testing:
– Model selection based on data type and checking conditions for specific models:
– t-test and t distribution (dependent and independent samples)
– Analysis of variance and F distribution
– Linear regression (forward, backward, stepwise)
– Analysis of qualitative data
– How to interpret odds ratio and relative risk
– Logistic regression
– What to do when conditions are not met? Nonparametric tests or alternatives