Basics of statistics and sample information:

It is a scientific way of analyzing, interpreting the organized data. The basic study of statistics starts with population and sample. A population is anything that is considered for study. A sample is portion of population collected to represent a population.

There are various technique of collecting sample from population.

Sampling methods can be classified into two categories:

    1) Probability sampling.
    2) Non-probability sampling.

Probability Sampling:

    1.Simple Random Sampling (SRS)
    2.Stratified Sampling
    3.Cluster Sampling
    4.Systematic Sampling
    5.Multistage Sampling (in which some of the methods above are combined in stages)

Simple Random Sampling - It is a sampling technique where each selected item or individual have a same probability of getting selected.

Stratified Sampling – It is a sampling technique where the population is divided into clusters, such that items within the cluster is homogeneous in nature and all the clusters are different from each other or heterogeneous in nature.

Cluster Sampling – It is a sampling technique where the population is divided into clusters. Each cluster is heterogeneous in nature meaning the items or individuals may be of different characteristics. A simple random sampling technique is used to collect sample from each of the clusters to collect a sample.

Systematic Sampling - Systematic sampling is a type of probability sampling method in which sample members from a larger population are selected according to a random starting point and a fixed periodic interval.

Multistage sampling refers to sampling plans where the sampling is carried out in stages using smaller and smaller sampling units at each stage.

    Non-Probability Sampling :

  • 1.Convenience Sampling :
  • - Where items/individuals or subjects are chosen according to convenience. They are simply chosen as they are easy to recruit or accessible to researcher. This sample technique is simple, least time consuming and cheapest.

  • 2.Consecutive Sampling :
  • It includes all the items or subjects that are available. That makes it a better representation of population.

  • 3.Quota Sampling :
  • - sampling technique wherein the researcher ensures equal or proportionate representation of subjects depending on which trait is considered as basis of the quota.

  • 4.Judgmental Sampling :
  • - subjects are chosen to be part of the sample with a specific purpose in mind. With judgmental sampling, the researcher believes that some subjects are more fit for the research compared to other individuals. This is the reason why they are purposively chosen as subjects.

  • 5.Snowball Sampling :
  • - s a non-probability sampling technique where existing study subjects recruit future subjects from among their acquaintances.

    For the following questions, answer true (t), false (f). Correct all false statements:

  1. The null hypothesis is always a statement of no effect.  T
  2. The binomial distribution describes the probability of getting "y" successes out of "n" tries when there are only two possible outcomes, and the probability of a success changes with each try.  F
  3. For the Analysis of Variance, all groups must have the same sample size.  F
  4. The sample mean is always a constant whereas the population mean is always a variable.  T
  5. The coefficient of skewness is a measure of location.  T