sampling

Sampling methodsGroup Name:

Wailay

Group members:

Malik Arsalan ALI khan 034

M.Saad

M.Shujahat 058

Khawar Abbas 056

Types of probability sampling

• Probability sampling

• Non probability sampling

Probability sampling

• A type of sampling in which every element of population has equal chance of selection

Types of probability sampling

• Simple random sampling

• Systematic random sampling

• Stratified random sampling

• Cluster sampling

Simple random sampling

• A method of probability sampling in which every unit has known and equal chance of being selected.

Method of simple random sampling

• With replacement

• Without replacement

Systematic random sampling

• A method of probability sampling in which the defined population is ordered and sample is selected by using skip interval.

Method of systematic random sampling

• Obtain the ordered list of units

• Determine number of units in list and desired sample size

• Determine the start point randomly

• Select sample by skip interval.

Stratified random sampling

• A method of sampling in which a population is divided into different subgroups and samples are drawn randomly.

Cluster sampling

• A method of sampling in which sampling units are selected in groups rather than individually.

Non probability sampling

• A method of sampling in which every element has unknown and unequal chance of selection.

Convenience sampling

• convenience sampling is a type of non probability sampling which involves the sample being drawn from that part of the population which is close to hand

Judgmental sampling

• the researcher chooses the sample based on who they think would be appropriate for the study. This is used primarily when there is a limited number of people that have expertise in the area being researched.

Quota sampling

• A quota is established (say 65% women) and researchers are free to choose any respondent they wish as long as the quota is met.

Snow ball sampling

• he first respondent refers a friend. The friend also refers a friend, and so on. Such samples are biased because they give people with more social connections an unknown but higher chance of selection

Sample design

• A methodological plan to obtain a sample from a given population.

Steps

• Types of population

• Sampling frame

• Sampling units

• Sampling methods

• Sampling size parameters

• Budgetary constraints

Characteristics of ideal sample design

• Must produce representative sample

• Must result in less sampling error

• Must be feasible in context of available funds.

• Should have results which can be applied to whole population.

• Should be able to prevent systematic bias.

Types of errors in sampling

• Sampling error

• Non sampling error

Sampling error

• The difference between a sample statistic and population parameters.

How to minimize sampling error sampling error

• Increasing sample size

• stratification

Non sampling error

• That does not occur due to sampling.

Reasons

• Improper division of sampling units

• Poor response of responses

• Bias

• Intentional bias

• Unintentional bias