A **population** is any specific collection of objects of interest.

A **sample** is any subset or subcollection of the population, including the case that the sample consists of the whole population, in which case it is termed a census.

A **measurement** is a number or attributes computed for each member of a population or of a sample. The measurements of sample elements are collectively called the sample data.

**“N”** is usually used to indicate the number of subjects in a study. Example: If you have 76 participants in a study, N=76.

A **parameter** is a number that summarizes some aspect of the population as a whole. A statistic is a number computed from the sample data.

**Quantitative data** are numerical measurements that arise from a natural numerical scale.

**Statistics** is a collection of methods for collecting, displaying, analyzing, and drawing conclusions from data.

**Correlation –** It is the degree to which two factors appear to be related. Correlation should not be confused with causation. Just because two factors are reported as being correlated, you cannot say that one factor causes the other. For example, you might find a correlation between going to the library at least 40 times per semester and getting high scores on tests. However, you cannot say from these findings what about going to the library, or what about people who go to libraries often, is responsible for higher test scores.

**Median** – The score that divides the results in half – the middle value.

**Descriptive statistics** is the branch of statistics that involves organizing, displaying, and describing data.

**Inferential statistics** is the branch of statistics that involves drawing conclusions about a population based on information contained in a sample taken from that population.

**r-value** is the way in which correlation is reported statistically (a number between -1 and +1). Generally, r-values should be >+/-.3 in order to report a significant correlation.

**Qualitative data** are measurements for which there is no natural numerical scale, but which consist of attributes, labels, or other nonnumerical characteristics.

Stay tuned to our website for more Statistics gyan..For puzzles, case studies and statistics question :-

100 puzzles and case studies to crack data science interview