Hence these methods are also called as Probability sampling methods. Probability is used in mathematical statistics to study the sampling distributions of sample statistics and, more generally, the properties of statistical procedures. Sampling can be done through various sampling techniques in accordance with the nature of the sample as well as the subject matter of the study. Formally, a 95% confidence interval for a value is a range where, if the sampling and analysis were repeated under the same conditions (yielding a different dataset), the interval would include the true (population) value in 95% of all possible cases. Interpretation often comes down to the level of statistical significance applied to the numbers and often refers to the probability of a value accurately rejecting the null hypothesis (sometimes referred to as the p-value). It is valuable in special circumstances. Populations can be diverse topics such as "all people living in a country" or "every atom composing a crystal".  Bar graphs are arguably the easiest diagrams to use and understand, and they can be made either by hand or with simple computer programs.  Some consider statistics to be a distinct mathematical science rather than a branch of mathematics. The psychophysicist Stanley Smith Stevens defined nominal, ordinal, interval, and ratio scales. Key Differences Between Population and Sample. 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 has modified the values of the measurements. For example if a sample constitutes 200 teachers, each teachers in the sample are considered as a sampling unit. The mathematical foundations of modern statistics were laid in the 17th century with the development of the probability theory by Gerolamo Cardano, Blaise Pascal and Pierre de Fermat. iii.  Misuse can occur when conclusions are overgeneralized and claimed to be representative of more than they really are, often by either deliberately or unconsciously overlooking sampling bias. Comptes Rendus Biologies (333) 134:144, Piazza Elio, Probabilità e Statistica, Esculapio 2007, Rubin, Donald B.; Little, Roderick J.A., Statistical analysis with missing data, New York: Wiley 2002, Nikoletseas, M.M. Interval measurements have meaningful distances between measurements defined, but the zero value is arbitrary (as in the case with longitude and temperature measurements in Celsius or Fahrenheit), and permit any linear transformation. In this sampling there is no means of judging the probability of the element or group of elements, of population being included in the sample. Such as male= 10, female=10; or science students=20and humanities students=20 and so forth. Descriptive statistics can be used to summarize the population data. Although in principle the acceptable level of statistical significance may be subject to debate, the p-value is the smallest significance level that allows the test to reject the null hypothesis. Initially, government can select any 10 states from different parts of the country. For example when a researcher intents to establish a favourable outcome over others, he may adopt biased sampling technique to ensure the indented results. Measurement processes that generate statistical data are also subject to error. A sample is simply a subset of the population. In social science and educational research, practically it is not possible to a researcher to approach all the individuals\elements in a population for the purpose of data collection. Convenience sampling is also called as haphazard as well as accidental sampling. Don't have time for it all now? A hypothesis is proposed for the statistical relationship between the two data sets, and this is compared as an alternative to an idealized null hypothesis of no relationship between two data sets. This is the reason why researchers rely on sampling techniques. Describe the advantage and limitations of stratified random sampling, Dr. RAFEEDALI.E, Assistant Professor,MANUU, CTE, Srinagar, 9419035681, email@example.com, Creative Commons Attribution 4.0 International License, I) Non-Random sampling techniques (Non- Probability Sampling), II) Random sampling techniques (Probability Sampling), i. "Government officials" is a well-defined group of individuals which can be considered as a population and all the members of this population are indeed officials of the government. However, due to the large sizes of populations, researchers often cannot test every individual in the population because it is too expensive and time-consuming.