Bshs 435 - Sampling and Data Collection

                                Sampling and Data Collection Research Paper

                                Michael Lawson

January 23, 2017

                                BSHS/435

                                Angela Heads

                        Sampling and Measuring Research Paper

Introduction

In human services it is crucial to understand the importance of observing a small group and different techniques that will not affect the measurement of the data or the reliability and validity of the study. This paper will identify sampling and data collection, as well as take a look at the sampling techniques, measurement methods, reliability and validity. It will also identify the advantages and disadvantages of, telephone surveys online surveys, focus groups, surveys via websites and I the author will decide which type of survey I would utilize if need be.

Sampling techniques

Sampling is to make the study feasible for the researcher to observe and study large groups of a population by breaking them down into smaller workable groups. By studying smaller groups, we can gain more accurate information from carefully drawn samples than we can from a large group, especially when the group under study is extremely large (thousands and millions).  While doing sampling it is important to avoid bias because if the researcher/s are partial in one way or another during the study they can ultimately play a role of having the studies outcome become inaccurate and unreliable. There are two types of sampling: Probability sampling – A method that uses random selections of participants in order to ensure that each element has an equal chance of inclusion. The methods used for this sampling include: Simple random, Systematic, Stratified, Area sampling and Estimating Sample Size (Monette, Sullivan, & DeJong, 2011). The other method is known as Nonprobability sampling – This method does not depend on random sampling, more so, the researcher is unaware of the probability of each population element’s inclusion in the sample, furthermore the nonprobability samples exist in order to see if a relationship exists between independent and dependent variables. Methods of nonprobability sampling include: Availability Sampling, Snowball Sampling, Quota Sampling, Purposive Sampling, Dimensional Sampling (Monette et, al. 2011).

Example of Probability and Nonprobability

A perfect example of probability sampling uses the Systematic approach which involves a table of numbers to decide on the random selection of participants inside the group. For example, Population N=100, Participants n=20, divide the two:  20/100= 5, select random integer between 1-5.  (using 4 for this example) the researcher would mark the participants from 1-100. Making a number table with 1 to 25 in first column, 26-50 in the second column and so forth till the researcher has 25 rows and 4 columns, the researcher would then take every 4th row and use the participants in those column until 20 participants are selected (William, 2006).  A perfect example of nonprobability can be seen using the Quota sampling model. In human services the researcher/s can pick multiple participants who meet certain criteria like age, race, sex, etc. and conduct interviews. They will determine the percentage the number of participants needed, say for instance 100 people, of these people 40% are women and 60% are men. Once you meet the 40% for women they will only conduct interviews on men until the 60% is met (William, 2006).