Sampling Lecture PDF

Sampling Objectives To understand: • Why we use sampling • Definitions in sampling • Sources of error • Main methods of sampling • Sample size calculation Definition of sampling Procedure by which some members of a given population are selected as representatives of the entire population Why d...

Sampling Objectives To understand: • Why we use sampling • Definitions in sampling • Sources of error • Main methods of sampling • Sample size calculation Definition of sampling Procedure by which some members of a given population are selected as representatives of the entire population Why do we use sampling? Get information from large populations with: ⚫ Reduced costs ⚫ Reduced field time ⚫ Increased accuracy Definitions Target population = the population to which the investigator wishes to generalize and from which sample is selected. Sample = a subset of the population selected in such a way that it is representative of the target population Definition of terms Sampling unit It is the unit from which the sample will be selected. It may be individuals, or groups of individuals as families, schools, … etc. Definition of terms Sampling frame It is a list of all sampling units in the target population which are given serial numbers starting with 1 and ending with N which equals the population size or total number of sampling units. It is a preliminary step to the selection of any sample. Sampling frame Serial number 1 2 3 4 5 N Names of sampling units ------------------------------------------------------------------------------------------------------------------------- Definition of terms Inquiry unit It is the unit from which or about which data will be collected. It may or may not be the same as the sampling unit. The same ➔ Sampling unit is family – Inquiry unit is family Different ➔ Sampling unit is family – Inquiry unit is child under 5 years. Definition of terms Response rate It is the percentage of people in the sample who actually participate in the study. Precision precision is a measure of the variability of the sample estimate Sources of Error Sampling (Random) Error It is the difference between the result of a sample, such as the sample mean, and the true value of the population, such as the population mean. Sources of Error Non Sampling (Systematic) error Non sampling errors arise from inaccuracies in the collection, recording and processing of data Types of sampling Non-probability samples Probability samples Non probability samples Convenience samples (ease of access) Snowball sampling (friend of friend….etc.) Purposive sampling (judgemental) ⚫ You chose who you think should be in the study Non probability samples Probability of selection cannot be determined Cheaper- but unable to generalise, potential for bias Probability Samples Sample where the probability of selection of each member can be determined and therefore results of sample can be generalized over the population Probability Samples Simple random sampling Systematic sampling Stratified sampling Multi-stage sampling Cluster sampling