In **cluster sampling**, groups of elements that ideally speaking, are heterogeneous in nature within group, and are chosen randomly. Unlike **stratified sampling** where groups are homogeneous and few elements are randomly chosen from each group, in **cluster sampling** the group with intra group heterogeneity are developed and all the elements within the group become a pan of the sample. Whereas **stratified sampling** has intra group homogeneity and inter group heterogeneity, **cluster sampling** has intra group heterogeneity.

## Examples

### One stage cluster sampling

A committee comprising of number of members from different departments has a high degree of heterogeneity. When from number of such committees, few are chosen randomly, and then it is a case of **one stage cluster sampling**.

### Two stage cluster sampling

If from each cluster which has been randomly chosen, few elements are chosen randomly using simple random sampling or any other probability method then it is a **two stage cluster sampling**.

### Multi-stage cluster sampling

A cluster sample can be a multiple stage sampling, when the choice of element in a sample involves selection at multiple stages e.g. if in a national survey on insurance products a sample of insurance companies is to be drawn, then it requires developing clusters at multiple stages.

In the first stage the clusters are formed on the basis of public and private companies. At the next stage a group of companies is chosen randomly from each cluster developed earlier. In the third stage the office location of each chosen company from where data is to be collected is chosen randomly. Thus in multistage sampling, probability sampling of primary units is done, then from each primary unit a sample of secondary sampling units is drawn and then the third levels till we reach the final stage of breakdown for the sample units.

Table of Contents

1.statistics adjusted rsquared

2.statistics analysis of variance

4.statistics arithmetic median

8.statistics best point estimation

9.statistics beta distribution

10.statistics binomial distribution

11.statistics blackscholes model

13.statistics central limit theorem

14.statistics chebyshevs theorem

15.statistics chisquared distribution

16.statistics chi squared table

17.statistics circular permutation

18.statistics cluster sampling

19.statistics cohens kappa coefficient

21.statistics combination with replacement

23.statistics continuous uniform distribution

24.statistics cumulative frequency

25.statistics coefficient of variation

26.statistics correlation coefficient

27.statistics cumulative plots

28.statistics cumulative poisson distribution

30.statistics data collection questionaire designing

31.statistics data collection observation

32.statistics data collection case study method

34.statistics deciles statistics

36.statistics exponential distribution

40.statistics frequency distribution

41.statistics gamma distribution

43.statistics geometric probability distribution

46.statistics gumbel distribution

49.statistics harmonic resonance frequency

51.statistics hypergeometric distribution

52.statistics hypothesis testing

53.statistics interval estimation

54.statistics inverse gamma distribution

55.statistics kolmogorov smirnov test

57.statistics laplace distribution

58.statistics linear regression

59.statistics log gamma distribution

60.statistics logistic regression

63.statistics means difference

64.statistics multinomial distribution

65.statistics negative binomial distribution

66.statistics normal distribution

67.statistics odd and even permutation

68.statistics one proportion z test

69.statistics outlier function

71.statistics permutation with replacement

73.statistics poisson distribution

74.statistics pooled variance r

75.statistics power calculator

77.statistics probability additive theorem

78.statistics probability multiplicative theorem

79.statistics probability bayes theorem

80.statistics probability density function

81.statistics process capability cp amp process performance pp

83.statistics quadratic regression equation

84.statistics qualitative data vs quantitative data

85.statistics quartile deviation

86.statistics range rule of thumb

87.statistics rayleigh distribution

88.statistics regression intercept confidence interval

89.statistics relative standard deviation

90.statistics reliability coefficient

91.statistics required sample size

92.statistics residual analysis

93.statistics residual sum of squares

94.statistics root mean square

96.statistics sampling methods

98.statistics shannon wiener diversity index

99.statistics signal to noise ratio

100.statistics simple random sampling

102.statistics standard deviation

103.statistics standard error se

104.statistics standard normal table

105.statistics statistical significance

108.statistics stem and leaf plot

109.statistics stratified sampling

112.statistics tdistribution table

113.statistics ti 83 exponential regression

114.statistics transformations

116.statistics type i amp ii errors

119.statistics weak law of large numbers