Statistics

Statistics is a field of study concerned with (1) the collection, organization summarization, and analysis of data; (2) the drawing of inference about a body of data when only a part of data is observed.

A descriptive measure computed from the data of a sample is called a statistic

A descriptive measure computed from the data of a population is called a parameter

Variable: A characteristic that takes different values in different persons, places or things.

Quantitative variable: that can be measured in the usual sense. Measurement convey information about amount.

Qualitative variable: measurement consist of categorization. Measurement convey information regarding attribute.

Random variable: when the values arise as a result of chance factor, so they cannot be predicted in advance 

Discrete variable: is characterized by gaps or interruptions in the values that it can assume 

Continuous variable: doesn’t possess the gaps or interruptions characteristic of a discrete variable

Population: largest collection of entities for which we have an interest at a particular time

Sample: a part of the population that we took for studying 

Measurement: assignment of numbers to objects or events according to as set of rules. Measurement may be carried out under different sets of rules

Measurement Scale: 

Nominal scale: naming the observations or classifying them into various mutually exclusive and collective exhaustive categories

Ordinal scale: when observations are not only from different categories but also can be ranked according to some criteria 

Interval scale: in addition to ordering the measurement we can also know the distance between the two measurements

Interval scale unlike the nominal and ordinal scales is a truly quantitative scale

Ratio scale: highest level of measurement. Equality of ratios as well as equality of the intervals may be determined. 

Fundamental to the ratio scale is true zero point

Simple random sample: If a sample of size “n” is drawn from a population of size “N” in such a way that every possible sample of size “n” has the same chance of being selected, the sample is called simple random sampling

As a rule, in practice, sampling is always done without replacement.

Systematic sampling: first we calculate the total number required for the sample, a random number table is then used to give a starting number (x). A second number determined by the sample size is selected to define the sampling interval (k). Now we select individuals in this way

x, x+k, x+2k, x+3k, …….

Stratified random sampling: population is stratified into strata. And a random sampling is taken in each strata.

PSM / COMMUNITY MEDICINE by Dr Abhishek Jaiswal is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Based on a work at learnpsm@blogspot.com.
Permissions beyond the scope of this license may be available at jaiswal.fph@gmail.com.