Descriptive Statistics
Descriptive statistics is used to summarize a collection of data in a clear and understandable manner. Measurements of an experiment can be summarized numerically or graphically. For the numerical approach, we compute the mean, standard deviation, etc. The graphical method involves box plots and stem and leaf displays. Numerical approach is generally more objective and precise while the graphical method is more useful for identifying patterns in data.
Descriptive statistics is looking at the data prior to formal analysis.
Inferential Statistics
Inferential statistics is used to draw inferences about a population from a sample. Statistical inferences can be made by either estimation or by hypothesis testing. In estimation, the sample is used to estimate a parameter and a confidence estimate. In hypothesis testing, we are interesting in finding whether we can reject a null hypothesis.
Variable
Variables are characteristics or attributes which can vary across different individuals.
Categorical or qualitative:
These variables are measured on a nominal scale. They have category names but no ordering e.g. black bear, polar bear, grisly bear, etc. Frequency
Numerical and quantitative:
These variables are measured on an ordinal (e.g. good, better, best), interval, or ratio scale. center and spread.
Numerical variable can be either discrete (exact numbers) or continuous (range).
For example, we ask a group of people to name their favorite actor, then the variable would be qualitative. The response time would be a quantitative variable.
A variable can be independent or dependent.