Variables
you gotta have Data! Data is the fuel that statistics runs on.
Statistics is the study of how to collect, organize, analyze, and interpret data
To get data you gotta measure, count or manipulate something. The thing you measure, count, or manipilate is called a variable.
In statistics variables come in several flavor pairs.
Quantitative.............................
Qualitative
Discrete...................................
Continuous
Independent............................Dependent
Qualitative variables are those variables in which an object or person can be placed into a category. The notion that one category is higher or lower than another must not make sense in this situation. Selecting people on the basis of eye color would be an example of using a qualitative variable. It makes no sense to say that having blue eyes is superior to having brown eyes.
Quantitative variables are used when you want to say how much or how little of a certain charasteristic one person has relative to another person. A persons weight is an example of a quantitative variable.
Quantitative variables can be further divided into two subgroups,
Descrete and Continuous. Continuous variables assume all real numbers between two given numbers. A persons weight is an example of a continuous variable, since weight can assume all values between zero and some specific number.
Descrete variables assume only whole number values such as 0,1,2,3, etc, The number of kittens in a litter is an example of a descrete variable.
The independent, dependent notion is used in situations in which one is interested in manipulating one variable (independent) and observing the effects on another variable (dependent). For example, a reseacher may want to know if keyboard styles (the independent variable) have an effect on typing speeds(the dependent variable).