Sampling Methods Worksheet

Sampling Methodologies

HCS/465

Team B

University of Phoenix Material

Sampling Methodologies

Research the sampling methodologies used in health care research covered in the textbook this week, and in other readings and resources. 

Review the Methods Map Visual Search Tool from Week One to help guide your research.

Part 1

List and provide a brief description of three types of probability and non-probability sampling methodologies (25 to 50 words each).

Probability Sampling Methodologies Non-probability Sampling Methodologies
1. Simple Random Sampling: This method of Probability Sampling is considered the best standard. For researchers, the process is conducted by analyzing each member of the population as an equal probability of selection into the sample. An example of this is flipping a coin. 1.
2. Sequential Sampling: This method of Probability Sampling is used by researchers and the process is conducted by picking a single or a group of subjects in a given time or set order. 2.
3. Stratified Sampling: This method of Probability Sampling is used by researchers, and the process is conducted by the researcher and divides the sample or population into separate groups, also called strata. Once grouped, the probability sample often chosen in the simple method is drawn from each group. 3.
4. Cluster Sampling: This method of Probability Sampling is used by researchers, and the process is conducted by the researcher who divides the sample or community into separate groups, also called clusters. Once grouped, the probability sample often chosen in the simple method is drawn from each clustered group.  

Answer the following prompt in 50 to 100 words:

Probability sampling means that the sample has a probability with each possible answer. Non-probability sampling means that there is no randomness or probability to the selection. Non-probable research methods can be both accidental or on purpose, meaning that the selection or outcomes were meant to happen, or that everything was done on purpose and with a specific plan in mind. Probability sampling provides that there is more of an experiment involved and can best represent the population by diagnosing the intervals and statistics during the research process (Trochim, 2006).

  • Explain the difference between probability and non-probability sampling methodologies.

Part 2

List and describe five types of data collection tools or instruments used in research (50 to 100 words each).

Data Collection Tools or Instruments Description of Data Collection Tools or Instruments
1. Focus Groups Focus groups are facilitated as a group interview with individuals that have something in common. This type of group is assembled to discuss or participate within a guided talk about certain topics or products that need feedback on the use of the product or experience with service. This type of data collection gathers information from a network of different perspectives or opinions. The responses from this collection are coded into categories for further analysis.
2. Ethnographies, Oral history, & Case studies This kind of data collection involves studying a single issue or topic, it then examines individuals within their normal environment. This kind of collection uses a many different techniques to accomplish its goal. These techniques can be observation, interviews, or surveys. Ethnography is a more holistic approach to evaluate versus the other three.
3. Interviews Using the interview approach is a good way to collect data in any research. They can be held either in person, over the phone, or through video conferencing. The preferred method to have an interview is face to face, versus a panel. These one on one interviews can be formal, semi-formal, or informal. With any collection of data, the interview questions should be clear, focused, and open ended.
4. Surveys or Questionnaires When we think of surveys we think of measured opinions or experiences from a group of people be asking multiple questions. Whereas questionnaires are usually printed with hand written or multiple-choice responses. These questions are for the solo purpose of a survey or statistical study.
5. Observation With Observation it allows the observer to study a person or group for the dynamics of any given situation. It also looks at the frequency counts of target behaviors or any behavior expected or not from the evaluation. This type of data collection usually produces both quantitative and qualitative information for review.

Part 3:

Identify three types of statistical analyses used in research and provide an example of each.

Type of Statistical Analysis Define the statistical analysis (25 to 50 words each) Example of statistical analysis
1. Descriptive Analysis Descriptive analysis is a type of quantitive analysis which, as its name suggests, summarizes and describes the basic features of data in a study. Descriptive analysis helps to break down large amounts of data into simpler form (Trochim, 2006). The GPA of every college student at a university describes the general performance of each student as they navigate through their college courses. This is a descriptive statistic.
2. Inferential Analysis Inferential analysis helps a researcher compare a sample to its population so that he/she can make conclusions. Inferential analysis helps a researcher to determine whether or not an observed difference between data is a dependable one or not (Trochim, 2006). Based on whether a student’s GPA is high, low, or mediocre, inferential analysis allows a researcher to conclude whether or not a student successful or not in college, but does not give information as to the difficulty of their courses, the course load that they are taking, or if they are juggling other activities concurrently.
3. Univariate Analysis Univariate analysis examines the distribution, central tendency, and/or the dispersion of data. The distribution of data tells the researcher the amount of times something occurred. Central tendency of a distribution is an estimate of the “center” of a distribution. Dispersion shows researchers the spread of the values around the central tendency, also knows as standard deviation (Trochim, 2006). Univariate analysis allows a researcher to group a large set of data into subset or groups so that it is easier to assess. For example, since GPA can range from 0.0 up to 4.0 or higher, a researcher can group their data into groups such as 0.0-0.9, 1.0-1.9, 2.0-2.9, 3.0-3.9, and 4.0 and up so that it is easier to determine things such as the mean, median, and mode of a set of data.

Cite at least 3 peer-reviewed, scholarly, or similar references to support your assignment. Use the resources in the University Library to ensure you have correctly cited your references.

Format your reference section and references used in your prompts and chart according to APA guidelines. Include a title page at the beginning of your worksheet.

Click the Assignment Files tab to submit your assignment.

References:

Cunningham, C. J. L., Weathington, B. L., & Pittenger, D. J. (2013). Understanding and conducting research in the health sciences.Retrieved from https://phoenix.vitalsource.com/#/books/9781118594360/cfi/6/30!/4/2/10/2@0:0https://phoenix.vitalsource.com/#/books/9781118594360/cfi/6/30!/4/2/10/2@0:0

Trochim, W. M. K. (2006). Web center for social research methods. Retrieved from https://socialresearchmethods.net/kb/sampnon.php

University of Minnesota. (2018). Data Collection Techniques. Retrieved from https://cyfar.org/data-collection-techniques

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