SOCW 6301 Week 7 Discussion

SOCW 6301 Week 7 Discussion

Discussion 1: Sampling Structures

Probability and nonprobability are the two general categories of sampling. Probability sampling uses random selection, whereas nonprobability sampling does not. For example, if you wanted to study the effects of divorce on the psychological development of adolescents, you could gather a population of a certain number of adolescents whose parents were divorced. Then, out of that population, you could randomly select 25 of those people. If you wanted to use nonprobability sampling, you would choose specific people who had met predetermined criteria. For this Discussion, consider how samples would be chosen for both probability and nonprobability sampling structures.

Post your explanation of the following:

•        Using your research problem and the refined question you developed in Week 4, develop two sampling structures: probability and nonprobability.
•        Explain who would be included in each sample and how each sample would be selected.
•        Be specific about the sampling structures you chose, evaluating both strengths and limitations of each.

Please use the resources to support your answer.

Methods of Measuring

The center point of research studies is the body of data collected to answer the research question. These data must be measured, which is the act of taking an abstract concept (e.g., depression, anger, etc.), sorting them out and quantifying them in some cohesive way in order to construct meaning—but how can you measure something that is not easily quantifiable?

Choosing an appropriate measurement tool requires consideration of a number of different issues including reliability, validity, appropriateness for use with a specific group or culture, availability, and potential cost. Sometimes, social workers will attempt to create their own set of questions to tap into or measure a concept. This may appear to be an easy thing to do; however, writing questions to measure a phenomenon is more challenging than it would seem. For example, how do we know it measures what we want it to measure?  In the first discussion this week, you will have the opportunity to create your own questions to measure a phenomenon of your interest. In the second discussion, you will compare the measure you created with an existing instrument that measures the same phenomenon.

To prepare: Choose one phenomenon or issue that a client may be dealing with (for example, depression, anxiety, or family conflict). Consider how you would evaluate the client’s progress in this area. Create questions with response options that would capture this phenomenon or client issue.

•        Identify the phenomenon you would measure and explain how you conceptualize this phenomenon.
•        Provide at least 3 questions you would use to measure this phenomenon and explain how these questions operationalize the phenomenon.
•        Define reliability in 2-3 sentences and give one example of how you would establish reliability for the questions you created.
•        Define validity in 2-3 sentences and give one example of how you would establish validity for the questions you created.
•        Create a measurement plan to assess the phenomenon.

o   Describe the methodology you would use to collect data using your measurement tool (your method for acquiring this research data).

o   Explain the advantages and disadvantages of your choices.

SAMPLE ANSWER

Sampling structures and methods of measuring

The purpose of this blog post is to introduce the concept of sampling and to explore some of the different structures and methods of measuring. Sampling is a process that is used in order to obtain information about a population. This can be done for a variety of reasons, such as to estimate the value of a parameter or to test a hypothesis. There are many different ways to go about sampling, and each has its own advantages and disadvantages. The most important thing is to choose the method that best suits your needs. In this blog post, we will take a look at some of the different methods of sampling and how they can be used.

What is Sampling?

There are many ways to collect data for research purposes. However, not all methods are created equal. In this blog post, we’ll be discussing sampling structures and methods of measuring in order to help you choose the best option for your project.

When it comes to sampling structures, there are two main types: probability and non-probability. Probability sampling is a method of selecting a sample from a population in which each member of the population has an equal chance of being selected. This is often done through random selection, such as using a random number generator. Non-probability sampling is a method of selecting a sample from a population in which some members of the population have more or less chance of being selected than others. This is often done through convenience sampling, such as selecting participants who are easily accessible.

Once you’ve decided on a sampling structure, you’ll need to choose a method of measuring. There are two main types of measurements: qualitative and quantitative. Qualitative measurements focus on characteristics that can’t be measured numerically, such as opinions or behaviors. Quantitative measurements focus on numerical data, such as age or income.

Both qualitative and quantitative measurements have their own strengths and weaknesses, so it’s important to choose the right type of measurement for your needs. If you’re unsure which type of measurement is right for you, please feel free to contact us and we’ll be happy to help you out.

Types of Sampling

There are two types of sampling: probability and non-probability. Probability sampling is when each member of the population being studied has an equal chance of being included in the sample. Non-probability sampling is when members of the population are selected for inclusion in the sample based on factors other than chance.

There are several different methods of probability sampling, including:
-Simple Random Sampling: This is when each member of the population has an equal chance of being selected for the sample.
-Systematic Sampling: This is when members of the population are selected at regular intervals.
-Stratified Sampling: This is when the population is divided into groups, or strata, and a simple random sample is taken from each stratum.
-Cluster Sampling: This is when the population is divided into groups, or clusters, and a simple random sample is taken from each cluster.

There are also several different methods of non-probability sampling, including:
-Convenience Sampling: This is when members of the population being studied are chosen because they are easy to access or reach.
-Purposive Sampling: This is when members of the population being studied are chosen because they have some characteristics that make them especially suited to provide information about a particular research question or hypothesis.
-Quota Sampling: This is when members of the population being studied

Simple Random Sampling

Simple random sampling is the most basic form of sampling. It involves selecting a unit from the population at random and then measuring it. This type of sampling is used when there is no clear structure to the population, or when the researcher wants to obtain a representative sample.

Stratified Sampling

There are two types of sampling structures: probability samples and non-probability samples. Probability samples are those in which each unit in the population has a known, non-zero chance of being included in the sample. In contrast, non-probability samples are those in which not all units in the population have a known, non-zero chance of being included in the sample.

A variety of methods exist for measuring variables of interest. The most common method is self-report, whereby respondents are asked to report on their own behaviors or characteristics. Other methods include observational data (e.g., people being observed while going about their daily activities), archival data (e.g., records that already exist, such as birth certificates or school transcripts), and physiological data (e.g., measures of heart rate or skin conductance).

Cluster Sampling

There are various types of sampling methods used in market research. Cluster sampling is one method that can be used when conducting a survey. This type of sampling is often used when it would be too costly or time-consuming to survey the entire population of interest.

With cluster sampling, the population is first divided into groups (clusters). A random sample of these clusters is then selected, and all members of the selected clusters are surveyed. The results from the cluster sample are then extrapolated to the population as a whole.

Cluster sampling can be an effective way to obtain a representative sample, but there are some potential drawbacks to this method. One drawback is that, because the clusters are not independent from each other, the variance of the estimates may be larger than with other methods (such as simple random sampling). Additionally, if the clusters are not carefully chosen, this method can introduce bias into the results.

Systematic Sampling

Systematic sampling is a type of probability sampling where the population is sampled in a systematic way. This means that every Nth member of the population is selected to be included in the sample, where N is the size of the population. Systematic sampling can be used with both simple random sampling and stratified sampling, and is often used when it is difficult to obtain a complete list of the population.

Multi-Stage Sampling

Multi-stage sampling is a type of probability sampling that is used when it is difficult or impossible to obtain a complete list of the population. In multi-stage sampling, the population is first divided into strata and then a sample is selected from each stratum. This process is repeated until all desired information has been collected. Multi-stage sampling can be used to select a representative sample from a large population.

Pros and Cons of each method

There are many different ways to measure something, and each has its own advantages and disadvantages. The most common methods are listed below, along with a brief description of the pros and cons of each:

-Anecdotal evidence: This is information that is based on someone’s personal experience or opinions. It can be useful in giving you a general idea of something, but it is not always reliable.

-Observation: This involves observing something directly and taking note of what you see. This can be useful in gathering data about things that are difficult to measure directly, but it can be biased if the observer is not impartial.

-Experimentation: This involves deliberately changing something and observing the results. This is the most reliable way to gather data, but it can be expensive and time-consuming.

-Surveys: This involves asking people questions about their opinions or experiences. Surveys can be quick and easy to administer, but they can be biased if the people surveyed are not representative of the population as a whole.

Conclusion

Sampling is a process of selecting a representative group from the population to estimate the characteristics of the whole population. The main purpose of sampling is to reduce the cost and time involved in data collection. There are various methods of sampling, and each has its own advantages and disadvantages. The type of study, the size of the population, and the resources available will all play a role in determining which method is best suited for a particular situation. In general, however, probability methods are considered to be more accurate than non-probability methods.