when might an entire population be used in a research study? course notes

What is the difference between the study population and study sample?

Chapter 52 Population Ecology. Lecture Outline. Overview: Earth’s Fluctuating Populations. To understand human population growth, we must consider the general principles of population ecology. Population ecology is the study of populations in relation to the environment, including environmental influences on population density and ...

Can the results of a particular study be generalized to population?

Determining Sample Size through Power Analysis: Need to have the following data: Level of significance criterion = alpha a, use .05 for most nursing studies and your calculations: Power = 1 - b (beta); if beta is not known standard power is .80, so use this when you are determining sample size Population size effect = gamma g or its equivalent, e.g. eta squared h 2; use …

What is population in statistics in research?

Yet as the source of evidence reached in a research study, a population may be more important than can be imagined. Credibility is of essence to every research study. Of course, if a study is not credible, the futility of efforts expended by the researcher, donor(s) and other stakeholders in executing it is evident. ...

Why is it not possible to study every unit of population?

investigators use only college students in their samples, yet their interest is in the adult population of the United States. To a large extent, the generalizability of sample data depends on what is being studied and the inferences that are being made. For example, imagine a study that sampled college juniors at a specific university.

When might an entire population be used in a research study?

When might an entire population be used in a research study? RATIONALE: When the population size is very small. The only time it makes sense to use an entire population is when the population is very narrowly identified and thus very small and accessible.

Why do we sample from an entire population?

Advantages and Disadvantages. Gleaning information from the total population often gives deeper insights into a target population than partial samples would be capable of. It has the potential to allow a researcher to paint a much more complete picture, and greatly reduces guesswork.May 10, 2018

Why is population important in research?

Having a sample that is representative of the target population is important for researchers to be able to generalize results found from observations of the sample to the target population.Dec 19, 2018

What is it called when you sample an entire population?

Total population sampling is a type of purposive sampling technique that involves examining the entire population (i.e., the total population) that have a particular set of characteristics (e.g., specific attributes/traits, experience, knowledge, skills, exposure to an event, etc.).

Why might a researcher use a sample rather than an entire population for their study?

It is efficient: When a sample is studied, instead of a whole population, it is a much quicker process and is more time efficient. It is practical: Most studies aim to make inferences about large populations. These populations are too large to collect data from each element within them.

Why is it not recommended to study the entire population?

The bottom line is it would be wasteful and foolish to use the entire population when a sample, drawn scientifically, provides accuracy in representing your population of interest. Assessing all individuals may be impossible, impractical, expensive or even inaccurate.

What is population in research Slideshare?

POPULATION  The entire aggregation of items from which samples can be drawn is known as a population.  In sampling, the population may refer to the units, from which the sample is drawn.  A population of interest may be the universe of nations or cities.

What is meant by study population in research?

Study population: The group of individuals in a study. In a clinical trial, the participants make up the study population. The study population might, for example, consist of all children under 2 years of age in a community.

What is a population in research methodology?

A research population is also known as a well-defined collection of individuals or objects known to have similar characteristics. All individuals or objects within a certain population usually have a common, binding characteristic or trait.

What is whole population?

countable noun. The population of a country or area is all the people who live in it.

What is a full sample?

A complete sample is a set of objects from a parent population that includes all such objects that satisfy a set of well-defined selection criteria. For example, a complete sample of Australian men taller than 2 m would consist of a list of every Australian male taller than 2 m.

What is the definition of a study population?

Study populations may be defined by geographic location, age, sex, with additional definitions of attributes and variables such as occupation, religion and ethnic group.[1] Geographic location.

What is population in statistics?

A population is a complete set of people with a specialized set of characteristics, and a sample is a subset of the population. The usual criteria we use in defining population are geographic, for example, “the population of Uttar Pradesh”.

What is the most challenging aspect of fieldwork?

The most challenging aspect of fieldwork is drawing a random sample from the target population to which the results of the study would be generalized. In actual practice, the task is so difficult that some sampling bias occurs in almost all studies ...

What is a case control study?

As opposed to descriptive studies where a study population is defined and then observations are made on a representative sample from it, in case control studies observations are made on a group of patients. This is known as the study group, which usually is not selected by sampling of a defined larger group.

Is field research difficult?

Field research is quite messy and difficult like actual battle. It may be sometimes difficult to get a sample which is truly random. Most samples therefore tend to get biased. To estimate the magnitude of this bias, the researcher should have some idea about the population from which the sample is drawn.

What is population ecology?

Population ecology is the study of populations in relation to the environment, including environmental influences on population density and distribution, age structure, and population size. Concept 52.1 Dynamic biological processes influence population density, dispersion, and demography. A population is a group of individuals ...

What is a population?

A population is a group of individuals of a single species that live in the same general area. Members of a population rely on the same resources, are influenced by similar environmental factors, and have a high likelihood of interacting with and breeding with one another.

How do populations evolve?

Populations can evolve through natural selection acting on heritable variations among individuals and changing the frequencies of various traits over time. Two important characteristics of any population are density and the spacing of individuals. Every population has a specific size and specific geographical boundaries.

What are the factors that affect crab populations?

Small changes in these variables cause large fluctuations in crab population numbers. Immigration and emigration can also influence populations.

What is natural selection?

Natural selection favors traits that improve an organism’s chances of survival and reproductive success. In every species, there are trade-offs between survival and traits such as frequency of reproduction, number of offspring produced, and investment in parental care.

Why are local densities important?

Variations in local density are important population characteristics, providing insight into the environmental and social interactions of individuals within a population. Some habitat patches are more suitable that others.

What is a population and sampling?

Populations. Definition - a complete set of elements (persons or objects) that possess some common characteristic defined by the sampling criteria established by the researcher. Composed of two groups - target population & accessible population. Target population (universe)

How many subjects are needed for central limit theorem?

As the number of variables studied increases, the sample size also needs to increase in order to detect significant relationships or differences. A minimum of 30 subjects is needed for use of the central limit theorem (statistics based on the mean) Large samples are needed if: There are many uncontrolled variables.

What is a sampling frame?

Sampling = the process of selecting a group of people, events, behaviors, or other elements with which to conduct a study. Sampling frame = a list of all the elements in the population from which the sample is drawn. Could be extremely large if population is national or international in nature.

What is the difference between probability and nonprobability sampling?

With nonprobability sampling, there is no way of estimating the probability of anelement’s being included in a sample. If the researcher’s interest is in generalizing the findings derived from the sample to the general population, thenprobability sampling is far more useful and precise. Unfortunately, it is also much more difficult and expensive than nonprobability sampling.Probability sampling is also referred to as random samplingor representative sampling. The word random describes the procedure used to select elements (participants, cars, test items) from a population. Whenrandom sampling is used, each element in the population has an equal chance of being selected (simple random sampling) or a known probability of being selected (stratified random sampling). The sample is referred to as representativebecause the characteristics of a properly drawn sample represent the parent population in all ways.

How is stratified random sampling used?

This procedure known as stratified random samplingis also a form of probability sampling. To stratify means to classify or to separate people into groupsaccording to some characteristics, such as position, rank, income, education, sex, or ethnic background. These separate groupings are referred to as subsetsor subgroups. For a stratified random sample, the population is divided into groups or strata. A random sample is selected from each stratum based upon the percentage that each subgroup represents in the population. Stratified random samples are generally more accurate in representing the population than are simple random samples. They also require more effort, and there is a practical limit to the number of strata used. Because participants are to be chosen randomly from each stratum, a complete list of the population within each stratum must be constructed. Stratified sampling is generally used in twodifferent ways. In one, primary interest is in the representativeness of the sample for purposes of commenting on the population. In the other, the focus of interest is comparison between and among the strata. Let’s look first at an example inwhich thepopulation is of primary interest. Suppose we are interested inthe attitudes and opinions of university faculty in a certain state toward faculty unionization. Historically, this issue has been a very controversial one evoking strong emotions on both sides. Assume that there are eight universities in the state, each with a different faculty size (faculty size = 500 + 800 + 900 + 1,000 + 1,400 + 1,600 + 1,800 + 2,000 = 10,000). We could simply take a simple random sample of all 10,000 faculty and send those in the sample a carefully constructed attitude survey concerning unionization. After considering this strategy, we decide against it. Our thought is that universities of different size may have marked differences in their attitudes, and we want to be sure that each university will be represented in the sample in proportion to its representation in the total university population. We know that, onoccasion, a simple random sample will not do this. For example, if unionization is a particularly “hot” issue onone campus, we may obtain a disproportionate number of replies from that faculty. Therefore, we would construct a list of the entire faculty for each university and then sample randomly within each university in proportion to its representation in thetotal faculty of 10,000. For example, the university with 500 faculty members would represent 5% of our sample; assuming a total sample size of 1,000, we would randomly select 50 faculty from this university. The university with 2,000 faculty would represent 20% of our sample; thus, 200 of its faculty would be randomly selected. We would continue until our sample was complete. It would be possible but more costly and time consuming to include other strata of interest—for example, full, associate, and assistant professors. Ineach case, the faculty in each stratum would be randomly selected.

Why is convenience sampling important?

Convenience samplingis used because it is quick, inexpensive, and convenient . Convenience samples are useful for certain purposes, and they require very little planning. Researchers simply use participants who are available at the moment. The procedure is casual and easy, relative to random sampling. Contrast using any available participants with random sampling, where you must (1) have a well-defined population, (2) construct a list of members of the population if one is not available, (3) sample randomly from the list, and (4) contact and use as many individuals from the list as possible. Convenience sampling requires far less effort. However, such convenience comes with potential problems, which we will describe. Convenience samples are nonprobability samples. Therefore, it is not possible to specify the probability of any population element’s being selected for the sample. Indeed, it is not possible to specify the population from which the sample was drawn.

What Is a Sampling Frame?

When developing a research study, one of the first things that you need to do is clarify all of the units (also referred to as cases) that you are interested in studying. Units could be people, organizations, or existing documents. In research, these units make up the population of interest.

Examples

Imagine that you're interested in examining customers' satisfaction with the service that they received at a local pizzeria since it opened one year ago. Once again, it would probably require too much time and money to collect this information from every person who has ever eaten at the pizzeria.