12.2:
Study Design in Statistics
Study designs are the framework for collecting and analyzing data in a particular study. They can be either descriptive or analytical.
A descriptive study describes one or more characteristics of a group, for example, the height of an orange tree or what are the personality traits of a successful industrialist. It is concerned with the question – what and not – why.
An analytical study establishes causal relationships among the variables and tests a hypothesis.
Analytical studies can be further divided into observational and experimental studies.
Observational studies describe how exposure and outcome occur naturally and measure variables of interest without influencing the response. For example, comparing the yield of oranges from two farms with different soil characteristics. This type of study would not manipulate soil or its properties.
In contrast, the experimental study actively manipulates the independent variables and measures the outcome or dependent variable. So researchers go back to the farms and see if suitable fertilizers can bring statistically significant improvements in the yield of oranges.
12.2:
Study Design in Statistics
A study design is a set of techniques that allow a researcher to collect and analyze data from different variables defined for a specific research problem. Statistics is commonly for effective study design and more robust experiments,
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper study design that ensures the production of reliable, accurate data.
There are two major types of study designs: descriptive and analytical studies. In descriptive studies, the variables are described and the question of what, rather than why, is answered. Analytical studies further divided into observational and experimental studies. In observational studies, the dependent and independent variables are analyzed without ever altering any variables. As an example, orange trees grow when they are exposed to sunlight. Road accidents and vehicle speed. Experimental studies influence or alter the independent variable and measure the outcome. The purpose of an experiment is to investigate the relationship between two variables. In a randomized experiment, the researcher manipulates values of the explanatory variable and measures the resulting changes in the response variable. The different values of the explanatory variable are called treatments. An experimental unit is a single object or individual to be measured.
This text is adapted from Openstax, Introductory Statistics, Section 1.4, Experimental Design and Ethics