What are researchers really referring to when they talk about the population
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If you had all the money and resources in the world, you could potentially sample the whole population. However, money and resources usually limit sampling, and furthermore all members of a population may not actually be identifiable in a way that allows you to sample. As a result, researchers take a sample, or a subgroup of people (or objects) from the population and study that instead of the population. In social scientific research, the population is the cluster of people, events, things, or other phenomena in which you are most interested. It is often the “who” or “what” that you want to be able to say something about at the end of your study. Populations in research may be rather large, such as “the Canadian people,” but typically they are more focused than that. For example, a large study, for which the population of interest really is the Canadian people, will likely specify which Canadian people, such as adults over the age of 18 or citizens or legal residents. Show
One of the most surprising and often frustrating lessons students of research methods learn is that there is a difference between one’s population of interest and one’s study sample. While there are certainly exceptions, more often than not, a researcher’s population and the sample are not the same. A sample is the cluster of people or events, for example, from or about which you will actually gather data. Some sampling strategies allow researchers to make claims about populations that are much larger than their actual sample with a fair amount of confidence. Other sampling strategies are designed to allow researchers to make theoretical contributions rather than to make sweeping claims about large populations. We will discuss both types of strategies later in this chapter. As mentioned previously, it is quite rare for a researcher to gather data from their entire population of interest. This might sound surprising or disappointing until you think about the kinds of research questions that sociologists typically ask. For example, suppose we wish to answer the following research question: “How do men’s and women’s college experiences differ, and how are they similar?” Would you expect to be able to collect data from all college students across all nations from all historical time periods? Unless you plan to make answering this research question your entire life’s work (and then some), the answer is probably “no.” So then, what is a researcher to do? Does not having the time or resources to gather data from every single person of interest mean having to give up your research interest? Absolutely not. It just means having to make some hard choices about sampling, and then being honest with yourself and your readers about the limitations of your study based on the sample from whom you were able to actually collect data. Click on this link to help you better understand how to get from the theoretical population (to whom you want to generalize) to your sample (who will actually be in your study) https://www.socialresearchmethods.net/kb/sampterm.php Now having said this, there are certainly times when it is possible to access every member of the population. This happens when the population is small, accessible, and willing to participate, or the researcher has access to relevant records. For example, suppose that a university dean wants to analyse the final graduating scores for all students enrolled in the university’s health sciences program, for 2015 to 2019. The dean wants to know if there is a trend toward an average increase in final graduating scores in health sciences, over this time period, as she suspects. Since the dean is only interested in her particular university and only those students who graduated from health sciences from 2015 to 2019, she can easily use the whole population. In this case, the population is the records of final graduating scores for all students enrolled in the university’s health sciences program from 2015 to 2019. To summarize, we use sampling when the population is large and we simply do not have the time, financial support, and/or ability (i.e. lack of laboratory equipment) to reach the entire population. In the following table you will find some examples of a population versus a sample, and the type of research methodology that might lead such a study. Do not worry about the methodology column now, as you have most likely not yet read the applicable chapters. Make a note to yourself and return to this table after reading Chapters 8 through 13. A population is the complete set group of individuals, whether that group comprises a nation or a group of people with a common characteristic. In statistics, a population is the pool of individuals from which a statistical sample is drawn for a study. Thus, any selection of individuals grouped by a common feature can be said to be a population. A sample may also refer to a statistically significant portion of a population, not an entire population. For this reason, a statistical analysis of a sample must report the approximate standard deviation, or standard error, of its results from the entire population. Only an analysis of an entire population would have no standard error. Key Takeaways
Understanding PopulationsIn most everyday uses, the word population implies a group of people or at least a group of living beings. However, statisticians refer to whatever group they are studying as a population. The population of a study might be babies born in North America in 2021, the total number of tech startups in Asia since the year 2000, the average height of all accounting examination candidates, or the mean weight of U.S. taxpayers. Statisticians and researchers prefer to know the characteristics of every entity in a population to draw the most precise conclusions possible. This is impossible or impractical most of the time, however, since population sets tend to be quite large. For example, if a company wanted to know whether most of its 50,000 customers were satisfied with the company's service last year, it would be impractical to call every client on the phone to conduct a survey. A sample of the population must be taken since the characteristics of every individual in a population cannot be measured due to constraints of time, resources, and accessibility. How to Calculate a PopulationA population can be defined narrowly, such as the number of newborn babies in North America with brown eyes, the number of startups in Asia that failed in less than three years, the average height of all female accounting examination candidates, or the mean weight of all U.S. taxpayers over age 30. The science of political polling offers a good example of the difficulty of selecting a random sampling of the population. One of the reasons why many of the last two presidential election polls have been wrong could be that the type of people who willingly answer poll questions may not constitute a random sample of the population of likely voters. Nonetheless, surveys and polls may be the only efficient way to identify and validate issues and trends that affect the wider population. For example, growing concerns have been expressed about harassment online, but how common is it? A study by Pew Research indicates that 41% of American adults have experienced online harassment, with 11% reporting they had been outright stalked, and 14% saying they had been physically threatened. Population vs. SamplesA sample is a random selection of members of a population. It is a smaller group drawn from the population that has the characteristics of the entire population. The observations and conclusions made against the sample data are attributed to the population as a whole. The information obtained from the statistical sample allows statisticians to develop hypotheses about the larger population. In statistical equations, the population is usually denoted with an uppercase N while the sample is usually denoted with a lowercase n. There are several ways to obtain samples (known as sampling) from a population. These include a simple random sample, stratified sampling, representative sampling, and convenience sampling. Researchers and analysts employ a range of statistical techniques to infer information about the broader population using just the smaller sample chosen. Note that sample size is an important issue when conducting such inference - if the sample is too small it may be biased and not trustworthy, while larger samples may be overly expensive and time-consuming to collect and analyze. As an illustration, assume that the population being studied is all of the zeroes depicted in the image below. The red circles form a sample of the population of all circles on the page.  Population ParametersA parameter is data based on an entire population. Statistics such as averages (means) and standard deviations, when taken from populations, are referred to as population parameters. The population mean and population standard deviation are represented by the Greek letters µ and σ, respectively. A valid statistic may be drawn from either a population sample or a study of an entire population. The objective of a random sample is to avoid bias in the results. A sample is random if every member of the whole population has an equal chance to be selected to participate. While a parameter is a characteristic of a population, a statistic is a characteristic of a sample. Inferential statistics enables you to make an educated guess about a population parameter based on a statistic computed from a sample randomly drawn from that population. The standard deviation, for example, is the variation of some variable in the population, which can be inferred from the variation observed in the sample. But, because this is being inferred from a sample, there will always be some sort of error term describing how likely it is that the analysis from the sample does not reflect the true standard deviation (or mean, etc.). Various statistical tools like confidence intervals, the t-test, and p-values can inform an analyst of how confident they might be in making such inferences. If you have the data for the entire population being studied, you do not need to use statistical inference from a sample, since you already know the population's parameters. The Demographic Meaning of PopulationWhile population can refer to any complete set of data in the statistical sense, population takes on another meaning when we talk about the demographic or geopolitical context. Here, a population refers to the entirety of the people inhabiting a particular region, country, or even the entire planet. Census counts keep track of the number of citizens that populate different counties along with their characteristics such as age, race, gender, income, occupation, and so on. Population counts are important for governments in order to collect taxes and allocate the proper amount of funding to various infrastructure and social programs. Demography is the study of populations and their characteristics, and how these change over time and from place to place. Population statistics and demographics inform public policy and business decisions. Some examples:
9.7 billionThe world's population by the middle of the 21st century, according to the United Nations. What Is Population in Research?The entire set of units (the universe of things) being studied is referred to collectively as the population. This can be a group of people, companies, organisms, government bonds, or anything else. What matters is that the population includes every one of those things. If randomly selected, a sample taken from the population can be used to study associations or attributes that may be representative of the larger population. For example, in a recent Gallup Poll, 57% of randomly selected 1,015 retirees said Social Security was a "major" source of their income. It can be concluded that most American retirees rely on Social Security, based on the responses of the population surveyed, but with a margin of error. What Will the World Population Be in 2050?The world population is expected to grow from 7.7 billion in 2019 to 9.7 billion in 2050, according to a projection by the United Nations Department of Economic and Social Affairs. The greatest growth is expected in sub-Sarahan Africa, where the population may double, while Europe and North America are expected to have the least growth, at just 2%. What Is 1% of the World's Population?The world's current population is estimated at 7.7 billion by the United Nations, so 1% of that would be 77 million. What Are the 10 Countries with the Largest Populations?China and India have by far the largest populations in the world, as of 2021, according to the World Bank. Here are the top 10 nations and their estimated populations:
Is Earth Overpopulated?The issue of overpopulation has been debated since at least 1786 when economist Thomas Malthus published his theory that the growth of the population will always outpace the growth in the food supply. This theory is known as Malthusianism. Malthus viewed the problem as an over-stretching of resources. Today's thinkers tend to give greater importance to the ethical and efficient distribution of resources. In any case, population trends are complex and their results are subject to debate. The population of the Earth has indisputably risen dramatically in the past 70 years, from under three billion in 1950 to nearly eight billion now. But birth rates have declined sharply in developed nations during the same period. The Bottom LineEach of us is an individual component of many populations. In addition to being members of the human population of Earth and citizens of a nation, we are members of many sub-populations based on age, gender, income, health status, and many other factors. When statisticians attempt to ascertain a fact or facts about any of those sub-populations, they typically rely on a sample population. These test subjects, selected at random, yield conclusions that are extended to the general population being studied. What does population refer to in research?A population is the entire group that you want to draw conclusions about. A sample is the specific group that you will collect data from. The size of the sample is always less than the total size of the population.
Why are samples used to make the conclusions about the population?In order to draw conclusions about the population in question, researchers generally draw a sample. The sample is a smaller number of cases or units; generally, the sample needs to be "representative" of the population in order for the researcher to draw conclusions.
How would you describe the population?A population is defined as a group of individuals of the same species living and interbreeding within a given area. Members of a population often rely on the same resources, are subject to similar environmental constraints, and depend on the availability of other members to persist over time.
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