While a common term for this activity is "data analysis" the activity actually has more in common with the ideas and methods of synthesis (putting things together) than it does in the original meaning of the term analysis (taking things apart). This is because the activity strives to bring the data structures of interest together in a cohesive, inseparable, whole by eliminating unnecessary data redundancies and relating data structures by relationships.
In the early phases of a software development project, emphasis will be on the design of a conceptual data model. This can be detailed into a logical data model sometimes called a functional data model. In later stages, this model may be translated into physical data model.
Statistical Methods
The basic goal of a statistical research project is to make a conclusion on the effect of changes of an independent variable on a dependent variable. There are two major types of statistical studies, experimental studies and post facto or after the fact studies. In both of these types of studies, the effect of changes of an independent variable on the behavior of the dependent variable are observed. The difference between the two is in how the study is actually conducted.
An experimental study involves taking measurements of the system under study, manipulating the system, and then taking additional measurements using the same procedure to determine if the manipulation may have modified the values of the measurements. A post-facto study involves reviewing existing data and making a determination about a correlation between two measurements.
There are four types of measurements or measurement scales used in statistics. The four types or level of measurement have different degrees of usefulness in statistical research. Typically, the most appropriate level of measurement is ratio measurement since ratio measurement provides the greatest flexibility in statistical methods that can be used for analysing the data. Interval measurement, such as IQ measurements or temperature measurements in degrees Celsius, is also used in statistical research.
Probability
The probability of an event is often defined as a number between one and zero. In reality however there is virtually nothing that has a probability of 1 or 0. You could say that the sun will certainly rise in the morning, but what if an extremely unlikely event destroys the sun? What if there is a nuclear war and the sky is covered in ash and smoke?
We often round the probability of such things up or down because they are so likely or unlikely to occur, that it's easier to recognize them as a probability of one or zero.
