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Sample And Data Collection Paper

1918 words - 8 pages



Sampling and Data Collection in Research Paper
Nykia Alford-Devezin
BSHS 435
April 5, 2016
Dr. Nicole Harris
Sample and Data Collection in Research Paper
In many ways, all research relies on observation. Research is empirical and by definition is perceived through the senses meaning, observed. Observation as a data collection method is underutilized in the human service field. In most cases, the person whose traits are being observed and the person performing the observation are different people. This deems observation less biased than other methods of data collection. Anastas (1999) brought to light that "we live in an age where observations are often a preferred form ...view middle of the document...

Nominal, ordinal, interval and ratio are levels of measurement that all refer to the relationship of values assigned to attributes for a variable. These levels of measurement are important because a researcher needs to see if there are differences in the data collected (Monette, Sullivan, & Dejong, 2011).
Nominal measurement gives a numerical value just to name an attribute uniquely. For example, a football player with the number 34 on his jersey is no more important than a player with the number 2 on his jersey. In ordinal measurement, the attributes are ranked in order. So if one was conducting a research study on cigarette smoking, capturing how many packs three smokers consume in a day the data could look like this: (1) three packs a day smoker (2) two packs a day smoker (3) one pack a day smoker. Another example of ordinal scaling is a level of agreement, no, maybe, yes or political orientation, left, center, right. The interval scale of measurement indicates the distance one object is from another. Examples of interval scaling are the time of day on a 12-hour clock and the temperature either measured in Fahrenheit or Celsius. A ratio scale has an absolute zero point of existence. It allows for comparison, such as a building being twice as high as the building sitting next to it. It also contains data from all three previous levels. Examples of ratio in measurement are a student's grade point average, a ruler in inches or centimeters, and years of work experience (Trochim, 2006). Each level of measurement possesses characteristics of the preceding levels, like nominal being the most simple, but the ratio is the most sophisticated.
Sampling is an important element of research, because of the impact that it can have on the quality of research findings. The main reason for sampling is to obtain a smaller piece of a larger population of data to be collected (Baran & Jones, 2016). Automakers in the U.S. have to demonstrate that their cars can survive certain crash test scenarios. Now the car company will not be able to crash every car in their inventory to demonstrate that they are safe, thus the reason they choose to crash only samples of cars. Sampling also lessens costs, time, and enhances more accurate results in sampling and inaccessibility of disadvantaged populations, e.g., prisoners, disaster survivors, people with severe mental illness, etc. A strong suit of sampling is that it enables ease of access to the data collected; petitioning many "diverse groups of smaller size" can translate more accurate results.
The importance of sampling is that a researcher or research group can determine sufficient results from a total number of target populations through surveying a smaller group within it. Thus, it will be used in a research study to warrant adequately generalities of the findings toward the target population. The advantages of sampling are, it is economical and practical, it produces faster data, decreases costs, and it yields...

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