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· Sampling: It is the procedure or process of selecting a sample from a population.
· Population: The group of individuals considered under study is called as population.
· Sample :Aselection of a group of individuals from a population.
· Sample size :The number of individuals included in a sample.
· Simple Random Sampling :The samples are selected in such a way that each and every unit in the population has an equal and independent chance of being selected as a sample.
· Stratified Random Sampling: When the population is heterogeneous, the population is divided into homogeneous number of sub-groups or strata. A sample is drawn from each stratum at random.
· Systematic Sampling: Select the first sample at random, the rest being automatically selected according to some predetermined pattern.
· Sampling Distribution: Sampling distribution of a statistic is the frequency distribution which is formed with various values of a statistic computed from different samples of the same size drawn from the same population.
· Standard Error: The standard deviation of the sampling distribution of a statistic is known as its Standard Error.
· Statistical Inference: To draw inference about a population of any statistical investigation from the analysis of samples drawn from that population.
· Estimation :The method of obtaining the most likely value of the population parameter using statistic is called estimation.
· Point Estimation: When a single value is used as an estimate, it is called as point estimation.
· Interval Estimation: An interval within which the parameter would be expected to lie is called interval estimation.
· Test of Statistical Hypothesis: Statistical technique to arrive at a decision in certain situations where there is an element of uncertainty on the basis of sampl
· Null Hypothesis: The hypothesis which is tested for possible rejection under the assumption that it is true”, denoted by H0.
· Alternative Hypothesis:The hypothesis which is complementary to the null hypothesis is called as the alternative hypothesis, denoted by H1 .
· Type I error: The error of rejecting H0 when it is true.
· Type II error: The error of accepting H0 when it is false.
· Test of significance for single mean:
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