Quantitative randomization and takes steps to ensure all

Quantitative Sampling that is data that can be counted or expressed numerically. It is commonly used to ask “how much” or “how many” and can be used to study events or levels of occurrence. Because it is numerical in nature, quantitative data is both definitive and objective. It also lends itself to statistical analysis and mathematical computations and therefore, is typically illustrated in charts or graphs. ( Laura M. O’Dwyer ; James A. Bernauer, 2014) SAGE Publications, Inc Quantitative Research for the Qualitative Researcher

Quantitative data collection may include ANY method that will result in numerical values. Common examples of quantitative data collection strategies may include:
•Experiments and clinical trials
•Surveys, interviews and questionnaires that collect numerical information or count data by using closed-ended questions
•Observing or recording well-defined events such as the number of visits patients make to a doctor’s office each year
•Obtaining information from a management information system.

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The advantage of collecting quantitative data is that the numerical outcomes result in data that can be statistically analyzed that may be viewed as credible and useful in decision making. However, the disadvantage of quantitative data is that it is superficial and therefore, it does offer solutions or assist in making predictions.

There are two main types of sampling: probability and non-probability sampling. The difference between the two types is whether the sampling selection involves randomization. Randomization occurs when all members of the sampling frame have an equal opportunity of being selected for the study. Following is a discussion of probability and non-probability sampling and the different types of each.

Probability Sampling – Uses randomization and takes steps to ensure all members of a population have a chance of being selected. There are several variations on this type of sampling and following is a list of ways probability sampling may occur:
•Random sampling – every member has an equal chance
•Stratified sampling – population divided into subgroups (strata) and members are randomly selected from each group
•Systematic sampling – uses a specific system to select members such as every 10th person on an alphabetized list

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