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Sampling (statistics)

Study Design

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Finally, interviewers often introduce bias when allowed to self select respondents, which is usually the case in this form of research. In choosing males , interviewers are more likely to choose those that are better-dressed, seem more approachable or less threatening.

That may be understandable from a practical point of view, but it introduces bias into research findings. Purposive sampling is a sampling method in which elements are chosen based on purpose of the study. Purposive sampling may involve studying the entire population of some limited group sociology faculty at Columbia or a subset of a population Columbia faculty who have won Nobel Prizes.

As with other non-probability sampling methods, purposive sampling does not produce a sample that is representative of a larger population, but it can be exactly what is needed in some cases - study of organization, community, or some other clearly defined and relatively limited group. This person is then asked to refer the researcher to yet another person, and so on. Snowball sampling is very good for cases where members of a special population are difficult to locate.

For example, several studies of Mexican migrants in Los Angeles have used snowball sampling to get respondents. The method also has an interesting application to group membership - if you want to look at pattern of recruitment to a community organization over time, you might begin by interviewing fairly recent recruits, asking them who introduced them to the group. Then interview the people named, asking them who recruited them to the group. The method creates a sample with questionable representativeness.

A researcher is not sure who is in the sample. It can be difficult to determine how a sample compares to a larger population. Also, there's an issue of who respondents refer you to - friends refer to friends, less likely to refer to ones they don't like, fear, etc.

As defined in the text random sampling requires sampling with replacement? A random sample can occur with or without replacement, depending on what makes more sense.

For instance, trying to calculate the odds of a dice roll would require a random sample with replacement because it is perfectly possible to get a 6 on each and every die ; trying to calculate the odds of a poker hand, however, would require random sampling without replacement the ace of spades can only show up once in any given round of dealing.

The only requirement for a random sample is that each object that might be chosen has a known and well-defined probability of being chosen at any given moment. For random samples with replacement that probability is always the same; For random samples without replacement that probability is determined by the objects that have previously been selected.

How would you define the sampling universe and why you chose this sample definition? What is the defining characteristic of a representative sample? It will represent the population as a whole. This is a great ideaif you the population is too large and you want to get a generalidea of how everyone will think. How do you define volume in design? Define job design How has management viewed job design since the Industrial Revolution?

What is "job design"? Job design refers to the way that a set of tasks, or an entire job, is organized. Job design helps to determine: It takes into account all factors which affect the work, and organizes the content and tasks so that the whole job is less likely to be a risk to the employee.

Job design involves administrative areas such as: A well designed job will encourage a variety of 'good' body positions, have reasonable strength requirements, require a reasonable amount of mental activity, and help foster feelings of achievement and self-esteem.

Job design principles can address problems such as: Job design is sometimes considered as a way to help deal with stress in the workplace. Job design and workplace design are often used interchangeably because both contribute to keep the physical requirements of a job reasonable.

Job design refers to administrative changes that can help improve working conditions. In comparison, workplace design concentrates on dealing with the workstation, the tools, and the body position that all influence the way a person does his or her work. Good workplace design reduces static positions, repetitive motions and awkward body positions. Good job design accommodates employees' mental and physical characteristics by paying attention to: Employees should have the option to vary activities according to personal needs, work habits, and the circumstances in the workplace.

Job design is an ongoing process. The goal is to make adjustments as conditions or tasks change within the workplace. Achieving good job design involves administrative practices that determine what the employee does, for how long, where, and when as well as giving the employees choice where ever possible.

In job design, you may choose to examine the various tasks of an individual job or the design of a group of jobs. Approaches to job design include: Job enlargement should add interest to the work but may or may not give employees more responsibility.

Job rotation moves employees from one task to another. It distributes the group tasks among a number of employees. Job enrichment allows employees to assume more responsibility, accountability, and independence when learning new tasks or to allow for greater participation and new opportunities.

Work Design Job Engineering: Work design allows employees to see how the work methods, layout and handling procedures link together as well as the interaction between people and machines. Job Analysis is a process to identify and determine in detail the particular job duties and requirements and the relative importance of these duties for a given job. Job Analysis is a process where judgments are made about data collected on a job.

There are two key elements of a job analysis: Identification of major job requirements MJRs which are the most important duties and responsibilities of the position to be filled. They are the main purpose or primary reasons the position exists. The primary source of MJRs is the most current, official position description. Most job analyses deal with KSAs that are measurable, that can be documented, and produce meaningful differences between candidates.

Typically, possession of KSAs is demonstrated by experience, education, or training. The goal of KSAs is to identify those candidates who are potentially best qualified to perform the position to be filled; they are most useful when they provide meaningful distinctions among qualified candidates. Source documents for KSAs may be the position description, HRM standard qualifications and job classification standards.

Duties and Tasks The basic unit of a job is the performance of specific tasks and duties. Information to be collected about these items may include: Environment This may have a significant impact on the physical requirements to be able to perform a job. The work environment may include unpleasant conditions such as offensive odors and temperature extremes. There may also be definite risks to the incumbent such as noxious fumes, radioactive substances, hostile and aggressive people, and dangerous explosives.

Tools and Equipment Some duties and tasks are performed using specific equipment and tools. Equipment may include protective clothing. These items need to be specified in a Job Analysis. Relationships Supervision given and received. Relationships with internal or external people.

Requirements The knowledges, skills, and abilities KSA's required to perform the job. While an incumbent may have higher KSA's than those required for the job, a Job Analysis typically only states the minimum requirements to perform the job.

What does or should the person do? What knowledge, skill, and abilities does it take to perform this job? What is the result of the person performing the job?

How does this job fit in with other jobs in the organization? What is the job's contribution toward the organization's goals? The process may seek to obtain information about the: Engineering Approach The most important single element in the Engineering approaches, proposed by FW Taylor and others, was the task idea, "The work of every workman is fully planned out by the management at least one day in advance and each man receives in most cases complete written instructions, describing in detail the task which he is to accomplish.

This task specifies not only what is to be done but how it is to be done and the exact time allowed for doing it. As advocated fragmentation and routinisation of work to reap the advantages of specialisation.

These principles to job design seem to be quite rational and appealing because they point towards increased organisational performance. Specialisation and routinisation over a period of time result in job incumbents becoming experts rather quickly, leading to higher levels of output. Despite the assumed gains in efficiency, behavioral scientists have found that some job incumbents dislike specialised and routine jobs.

Human Relations Approach The human relations approach recognised the need to design jobs in an interesting manner. In the past two decades much work has been directed to changing jobs so that job incumbents can satisfy their needs for growth, recognition and responsibilility, enhancing need satisfaction through what is called job enrichment.

One widely publicised approach to job enrichment uses what is called job characteristics model and this has been explained separately in the ensuing section. Two types of factors, viz. The employee is dissatisfied with the job if maintenance factors to the required degree are not introduced into the job. But, the employee may not be satisfied even if the required maintenance factors are provided.

The employee will be satisfied with his job and he will be more productive if motivators are introduced into the job content. As such, he asserts that the job designer has to introduce hygienic factors adequately to reduce dissatisfaction and build motivating factors. Thus, THE emphasis is on the psychological needs of the employees in designing jobs.

The Job Characteristics Approach The Job Characteristics Theory states that employees will work hard when they are rewarded for the work they do and when the work gives them satisfaction. Hence, they suggest that motivation, satisfaction and performance should be integrated in the job design. According to this approach, any job can be described in terms of five core job dimensions which are defined as follows: The degree to which the job requires that workers use a variety of different activities, talents and skills in order to successfully complete the job requirements.

The degree to which the job allows workers to complete whole tasks from start to finish, rather than disjointed portions of the job. The degree to which the job significantly impacts the lives of others both within and outside the workplace. The degree to which the job allows workers freedom in planning and scheduling and the methods used to complete the job. There are two main types of sampling: The difference between the two types is whether or not 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:. Non-probability Sampling — Does not rely on the use of randomization techniques to select members.

This is typically done in studies where randomization is not possible in order to obtain a representative sample. Bias is more of a concern with this type of sampling. The different types of non-probability sampling are as follows:. The following Slideshare presentation, Sampling in Quantitative and Qualitative Research — A practical how to, offers an overview of sampling methods for quantitative research and contrasts them with qualitative method for further understanding.

Examples of Data Collection Methods — Following is a link to a chart of data collection methods that examines types of data collection, advantages and challenges. Qualitative and Quantitative Data Collection Methods - The link below provides specific example of instruments and methods used to collect quantitative data.

Sampling and Measurement - The link below defines sampling and discusses types of probability and nonprobability sampling. Principles of Sociological Inquiry — Qualitative and Quantitative Methods — The following resources provides a discussion of sampling methods and provides examples.

This would be considered a failure in internal validity. Another type of systematic sampling error is coverage error , which refers to the fact that sometimes researchers mistakenly restrict their sampling frame to a subset of the population of interest.

This means that the sample they are studying varies systematically from the population for which they wish to generalize their results. This leaves out all of the more rural populations in developing countries, which have very different characteristics than the urban populations on several parameters. Thus, the researcher could not appropriately generalize the results to the broader population and would therefore have to restrict the conclusions to populations in urban areas of developing countries.

First and foremost, a researcher must think very carefully about the population that will be included in the study and how to sample that population. Errors in sampling can often be avoided by good planning and careful consideration. However, in order to improve a sampling frame, a researcher can always seek more participants.

The more participants a study has, the less likely the study is to suffer from sampling error. In the case of the response rate problem, the researcher can actively work on increasing the response rate, or can try to determine if there is in fact a difference between those who partake in the study and those who do not.

The most important thing for a researcher to remember is to eliminate any and all variables that the researcher cannot control. While this is nearly impossible in field research, the closer a researcher comes to isolating the variable of interest, the better the results. Conducting Research in Psychology: Measuring the Weight of Smoke, 3rd Edition. Wadsworth Publishing February 27, All Rights Reserved Worldwide.

Privacy Policy Information Disclaimer. Study Design and Sampling Study Design Cross-sectional studies are simple in design and are aimed at finding out the prevalence of a phenomenon, problem, attitude or issue by taking a snap-shot or cross-section of the population.

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Probability sampling is a technique wherein the samples are gathered in a process that gives all the individuals in the population equal chance of being selected. Many consider this to be the more methodologically rigorous approach to sampling because it eliminates social biases that could shape the research sample.

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In simple random sampling, every member of the population has an equal chance of being chosen. The drawback is that the sample may not be genuinely representative. Small but important sub-sections of the population may not be included. Researchers therefore developed an alternative method called stratified random sampling. This method .

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Module 2: Study Design and Sampling Study Design Cross-sectional studies are simple in design and are aimed at finding out the prevalence of a phenomenon, problem, attitude or issue by taking a snap-shot or cross-section of the population. The purpose of this paper is to provide a typology of sampling designs for qualitative researchers. We introduce the following sampling strategies: (a) parallel sampling designs, which represent a body of sampling strategies that facilitate credible comparisons of two or more different subgroups that are extracted from the same levels of study; (b) nested sampling designs, which are sampling.

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Sampling method refers to the rules and procedures by which some elements of the population are included in the sample. Some common sampling methods are simple random sampling, stratified sampling, and cluster sampling. hi, thank you for sharing your slides on sampling design, I find them very useful material for my course on research methods. Best to you.