# Sample and Sampling

The following definitions give insights into sampling.

According to **Cooper and Schindler,** “*Sampling is some elements Of population which help to draw conclusions about the entire population.*“

According to **U. Sekaran,** “*Sampling is a process of selecting sub-set of the population by the study of which a researcher would be able to draw conclusions that would be generalizable to the populations.*“

According to

**P.V. Young,**“

*A statistical sample is a miniature picture or cross-section of the entire group or aggregates from which sample is taken, the entire group from which sample is chosen is known as the population or universe.*“

## Reasons for Selecting Sample

There are several reasons for sampling. They are explained below:

#### 1. Lowers cost:

#### 2. Provides greater accuracy:

#### 3. Helps to greater speed of data collection:

#### 4. Inaccessible population:

## Factors affecting the Size of the Sample

#### 1. Homogeneity/heterogeneity of universe:

#### 2. Number of classes proposed:

#### 4. Practical consideration:

#### 5. Standard of accuracy:

#### 6. Nature of cases to be contacted:

#### 7. Type of sampling used:

*Key Components:-*

*Sample and Sampling in research | Reasons for Selecting Sample | Factors Affecting the Size of the Sample | The Sampling process | Types of Sampling*

## The Sampling Process

### 1. Define the population:

### 2. Specify the sampling frame:

### 3. Specify sampling unit:

### 4. Determination of Sample Size (n):

#### a. Using a sample size of a similar study:

#### b. Using published tables:

#### c. Using statistical formulae:

### 5. Preparation of plan for sampling:

### 6. Select the sample:

## Types of Sampling

### 1. Probability Sampling

#### a. Simple random sampling:

#### b. Systematic sampling:

*Sampling interval (K)*- List the total number of units in the population.
- Decide the sample size (n).
- Calculate the sampling interval. Sampling interval =N/n
- Identify the random start of the first number selected from the population.
- Draw a sample by using a sampling interval.

#### c. Stratified sampling:

- Determine the variables to use for stratification.
- Determine the proportions of the stratification variables in the population
- Select proportionate or disproportionate stratification based on information needs and risk.
- Divide the sampling frame into separate frames for each group
- Follow random or systematic procedures to draw the sample from each group.

### d. Cluster sampling:

### 2. Non-Probability Sampling

#### a. Purposive or judgmental sampling:

#### b. Quota sampling:

- Classify the population into different classes based on demographic factors i.e. age, sex, income level, etc.
- Determine the number of samples to be selected from each class.
- Select the sample based on a pre-determined number from each class.

#### c. Convenience sampling:

#### d. Self-selecting sampling:

#### e. Snowball sampling:

- Finding out the first person from the population who can give information about the subject under study.
- Ask to refer to other persons who can give information about the subject under study.
- If a further sample is not found or sample formed a large number of person then close the sampling work.

## Descriptions of Various types of samples are summarized below:

Types of Sampling | Brief Description |
---|---|

A. Probability Sampling | – |

a. Simple random sampling | All elements in the population are considered and each element has an equal chance of being chosen as the subject. |

b. Systematic sampling | Every nth element in the population is chosen stating from a random point in the population frame. |

c. Stratified sampling | Population is first divided into meaningful segment and samples are selected in proportionate or disproportionate way from each meaningful segment. |

d. Cluster sampling | Groups that have heterogeneous members are first identified then some are chosen at random. Members in each of the randomly chosen groups are studied. |

B. Non-Probability Sampling | – |

a. Purposive or judgmental sampling | Subjects selected on the basis of their expertise in the subject investigated. |

b. Quota sampling | Subjects are conveniently chosen from target groups accordingly to some predetermined number or quota. |

c. Convenience sampling | The most easily accessible members are chosen as samples. |

d. Self-selecting sampling | Selecting the sample based on the response provided spontaneously.. |

e. Snowball sampling | Selecting few or single sample at first and obtaining other sample units on the basis of their reference. |