Sampling Techniques
A sampling procedure that assures that each element in the population
has an equal chance of being selected is referred to as simple random
sampling .Let us assume you had a school with a 1000 students, divided
equally into boys and girls, and you wanted to select 100 of them for
further study. You might put all their names in a drum and then pull
100 names out. Not only does each person have an equal chance of being
selected, we can also easily calculate the probability of a given
person being chosen, since we know the sample size (n) and the
population (N) and it becomes a simple matter of division:
n/N x 100 or 100/1000 x 100 = 10%
Systematic Sampling
At first sight this is very different. Suppose that the N units in the
population are numbered 1 to N in some order. To select a systematic
sample of n units, if $k approx N/n$then every k-th unit is selected
commencing with a randomly chosen number between 1 and k. Hence the
selection of the first unit determines the whole sample, e.g., N =
5,000, n = 250 therefore k = 5000/250 = 20. Therefore, select every
20th item commencing with (say) 6.
Question : Is it equivalent to simple random sampling? Strictly
speaking the answer is No!, unless the list itself is in random order,
which it never is (alphabetical, seniority, street number, etc).
Advantages
(i)
easier to draw, without mistakes (cards in file)
(ii)
more precise than simple random sampling as more evenly spread over
population
Disadvantages
(i)
if list has periodic arrangement then it can fare very badly
Stratified Sampling
In this random sampling technique, the whole population is first into
mutually exclusive subgroups or strata and then units are selected
randomly from each stratum. The segments are based on some
predetermined criteria such as geographic location, size or
demographic characteristic. It is important that the segments be as
heterogeneous as possible.
Purposeful non-probability sampling was used in this research study. The study was post-test only with no random assignment. The ExCEL program’s electronic database files were used to
The spreadsheet from the eLearn titled “Experiment I data” was downloaded to the computer. There were three inhibitors data given. The slope (V0) was calculated for each inhibitor data using the time versus response. The formula used to calculate slope was typed = slope (B6:B11, $A$6: $A$11) in the cell right below the last Reponses, and then from that cell dragged horizontally to get the rest of the slope. This step was repeated for Inhibitor 2, and 3 data.
Having a large sample size in a survey does not assure accurate statistics. What really matters is the sample diversity. For example: you wanted to find out how many of your workmates watch football, it would be foolish to only survey the men in your office and assume that the statistic applies for all the company’s employees. In order to get accurate statistics, you would have to expand the survey to include the female employees and the workers in other company offices.
In any healthcare organization, data is collected in numerous ways for an ever-increasing number of reasons. Data may be collected by a monitoring device directly connected to the patient, or by providers as they make observations or record treatments. Quality improvement activities often call for data collection where observations of activities, timeliness, or satisfaction indicators are gathered. Data may be abstracted from primary sources and collected for unique reporting requirements, such as specialized registries or claims transactions. With the various types of data collected in many different methods for varied purposes, it is not surprising that data collection may have escaped management in the past.
Two sampling methods include mail surveys and convenience sampling, a variation of a nonprobability sample. Mail surveys, inexpensive way to contact individuals over a large geographical area, provide anonymity to the respondent, and eliminate interview bias. Convenience sampling, a nonprobability sample, the only criteria is the convenience of the unit to the researcher, fast and uncomplicated, but the sampling error not determined.
...ristics such as age, race, gender, education etc. The only way to use this sample is if other methods are not available. In order for a purposive sampling approach to be successful, researchers need to be careful and not use results from previous convenience samples (Purposive sampling, 2012).
After randomly choose the sample group. The 60 students will then be randomly assigned to 2 groups...
Data acquisition is the process of copying data. For computer forensics, it’s the task of collecting digital evidence from electronic media. There are two types of data acquisition: static acquisitions and live acquisitions.
Sampling bias (pg. 112) – a sampling method can be called biased if the results of the research found favors the outcome the researcher is looking for. The researcher ultimately controls/influences whether the results are biased and potentially misleading. If a researcher thinks that football players are more susceptible to concussions, the researcher may only look at specific positions where the players take more hits to the head for their research which could affect the results looking at football players as a whole.
In order to effectively address a proposed research’s problem or research question(s), the researcher adopt a wide range of qualitative and quantitative mythologies (Berndtsson, Hansson, Olsson, & Lundell 2008). Some of these methodologies include interviews (Jones 1985), questionnaires, and surveys (Dawson 2009). Various qualitative and quantitative methodologies have distinct advantages and limitations which can be optimized if researchers correctly identify the most appropriate method for collecting a particular type of data.
1. Quantitative methods are mostly used through numerical data, which means it is countable and it comes from a data collection. So I personally think,the best topics to be studied would be, students not finishing their studies or the increasing number of minor 's crimes. On the other hand, qualitative methods could be used to formulate new research questions when a quantitative method research seems difficult to generate new hypotheses and ideas. The qualitative methods present facts and figures through observations and interviews. The topics I would be studied for qualitative methods are people 's experience with food and body image and also one of the most important one why people decide to take loans in order to pay their education.
Often uses random sampling to select a large statistically representative sample from which generalizations can be drawn.
To collect valid and reliable data for the investigation, the researcher combined qualitative and quantitative methods to conduct “mix methods research” (Creswell, Plano, Gutmann & Hanson, 2003, p.42) because Dörnyei (2007) claimed that qualitative and quantitative methods had equal contribution in theorising as they can support each other. Furthermore, the two methods were adopted to attain an entire understanding of a target phenomenon or to justify one series of results against the other (Sandelowski, 2003). As regards quantitative and qualitative methods, according to Conrad & Serlin (2011), qualitative research methods paid attention to exploring the experiences, perspectives, and mindsets of the participants. In other words, the qualitative
The key to good research is preparation, preparation, and preparation. Hence, the key to making good sampling choices is preparation. Trochim (2008) defines sampling as the drawing of a sample (a subset) from a population (the full set). In our everyday lives we all draw samples without realising it. For instance, when one decides to taste some unfamiliar food or drink that is some form of sampling. Williams (2003 74) posits that “Sampling is a search for typicality). On the other hand, (Clark: 2006 87) defines sampling as “a process of drawing a number of individual cases from a larger population”. According to (Chiromo: 2006 16), “a sample is a smaller group or subset of the population”.
The sampling design process includes five steps which are closely related and are important to all aspect of the marketing research project. The five steps are: defining the target population; determining the sample frame; selecting a sampling technique; determining the sample size; and executing the sampling process.