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Sampling and Date Collection

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Sampling
A sample is drawn from a population, which refers to all possible cases of what the researcher is interested in studying. A sample consists of one or two elements selected from a population. To select a good sample we have to clearly define the population from which we will be drawing a sample. Failure to do so can result in inaccurate conclusions. In probability sampling each element has an equal chance of inclusion. The simplest technique for probability samples is Simple Random Sampling. Simple random sampling treats the target population as a unitary whole. We might start off with a sampling frame which has a list of the whole population—or as much information as we can obtain. Next we would number the elements in the sampling frame sequentially and select elements from the list randomly. We would not know what the outcome would be, but each has an equal shot at being chosen. We can also program the computer to choose a random sample. Researchers may also use non probability sampling. In this type of sampling the researcher does not know the probability of each population’s elements inclusion in the sample (Dejong, 2011).

Data Collection
There are many different ways to collect data for research. Measures differ from one another in terms called levels of measurement. Nominal measures classify observations into mutually exclusive and exhaustive categories. They represent nominal variables such as sex, ethnicity, religion, and political party preferences. For the purpose of data collection a number might be assigned to each category. Ordinal measures are at a higher value then nominal numbers because categories have a fixed order. Interval measures share the characteristics of ordinal scales, mutually exclusive and exhaustive categories and an inherit order, but have equal spacing between the categories. Degrees on a temperature scale are part of the measurement. The common temperature scales are Fahrenheit and Celsius, both scales have units of measurement, degrees, and equal spacing that is characteristic of interval scales. Ratio measures are the highest level of measurement. It shares all the characteristics of interval measures, but the zero point is absolute and meaningful ratherthan arbitrary. A ratio variable which Human service workers are likely to work with is income. Four different scales are used for measurement because not all data is the same. Measurement devices are chosen on the basis of theoretical considerations, their validity and reliability, their level of measurement, the amount of systematic and random errors, and feasibility.
Measures
Measures are evaluated in terms of their reliability, which means the measures ability to produce consistent results each time it is applied. Many techniques exist in estimating the reliability of a measure, which are based on two principles, stability and equivalence. Stability is the idea that one reliable measure will not change from one application to the next, assuming that the concept being measured has not changed. Equivalence is the idea that all items that make up a measuring instrument should measure the same thing, and be consistent with each other. Measures are also evaluated in there terms of validity, which relates to the accuracy of a measure(Dejong, 2011).
It is important that data collection materials and instruments are reliable and valid because it affects how research results turn out. If the instruments used are not accurate and don’t reflect the correct information that data you collect will be invalid and have many errors. Therefore your conclusion would be inaccurate. There are many ways to collect data such as telephone surveys, online surveys, focus groups, and surveys via websites. Each of these methods has advantages and disadvantages. Telephone surveys are less expensive than face to face interviews. Disadvantages would be that telephone surveys require less time, which means less information is taken in by the researcher. Telephone interviews also lack visual contact, which means the interviewee cannot supplement responses with observational information. Online surveys are also cheap to conduct and are fast and have the ability to reach anywhere in the world. Disadvantages are not everyone has access to a computer or internet. Also not many people are willing to fill out an online survey. Focus groups have advantages such as a large number of people can answer questions at the same time. Focus groups also have a high level of participation, unfortunate data is more difficult to analyze. There are many types of validity, which refers to the measures ability to measure accurately. Face validity refers to accessing whether a logical relationship exist between the variable and the proposed measure. Is this the right measurement to use to reflect the variable? This type should be the starting point in determining validity, but is also the weakest form. The next type of validity is called content validity, which focuses on whether a measuring device covers the full range of meanings or forms that are included in a variable to measure. The third type of Validity is criterion establishes validity by showing a correlation between a measurement device and some other criterion or standard that we know or believe accurately measures the variable under consideration.

Resources
Monette, D. R., Sullivan T. J., &DeJong, C. R. (2011). Applied social research: A tool for the human services (8th ed.). Belmont, CA: Brooks/Cole.

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