Sampling assignment help

Sampling assignment help

Sampling can be defined as the process of picking or selecting a group of objects or people from a larger group of items or a population with the intent of studying and characterizing the larger group. When researchers want to study a certain group of people, it can be impossible to collect information from each and every individual in the group. Hence, they select a sample to represent the larger group and the few chosen individuals are the ones who will actually take part in the research.

For researchers to obtain the most reliable data and draw valid conclusions, they have to decide the best way to pick a sample that represents the entire group. They are two major types of sampling techniques:

  • Probability sampling: Involves selecting the sample randomly allowing the researcher to draw statistical inferences about the entire group.
  • Nonprobability sampling: Involves selecting the sample based on convenience or any other criteria that will allow the researcher to collect initial data easily.

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Population versus sample

Population is the whole group that you wish to study and draw conclusions about, while a sample is the group of people from which you will be gathering your data. A population can be obtained based on various characteristics including income, age, gender, geographical location, etc. It can be as broad or as narrow as the researcher wishes it to be depending on the characteristics being observed. It is important for one to define his/her target population carefully according to what the project aims toachieve. If the population is quite large, geographically dispersed, or demographically mixed, it can be difficult to obtain a good sample.

The sampling process

So you want to select a group of people to participate in your research? Our sampling project help experts suggest following the steps below:

  1. Identify your prospective population: As stated above, a population is the larger group of individuals you want to draw conclusions about. For instance, you may want to study patients with diabetes. Your population is every patient who suffers from this condition across the world because this is what you are interested in. Obviously, there is no way you can feasibly research about every patient with diabetes in the world, so you will move on to the next step.
  2. Identify a sampling frame: The group of individuals from which you will select your sample is called a sampling frame. For instance, you may decide that your sampling frame is every person with diabetes in the city where you live. Note that a sampling frame will not be as large as the population you intend to draw inferences about, but it should still be a relatively large group of people. Of course, you still will not be able to examine every person living with diabetes in your area but this is a great place to draw your sample. If you would like to learn more about choosing a sampling frame, connect with our online sampling tutors.
  3. Choose a sampling method: As mentioned earlier, there are two ways though which you can select your sampling frame; randomly or non-randomly. If your sampling frame has similar demographic makeup to the population you intend to study, then you can select your sample randomly. On the other hand, if the sampling frame does not fully represent the larger population, for instance, if there are more men than women in your city than in other cities in the world and you feel that this could affect your results, you would be better off selecting your sample non-randomly. If you wish to have these two sampling methods explained further by a professional, liaise with our sampling assignment help service providers.
  4. Identify the sample size: Generally, working with larger samples is better, but larger samples will also require more work and time to manage. If you end up having to prepare a thousand surveys, it will take you more time than if you only have to prepare one hundred surveys. Nevertheless, the results obtained from the one thousand surveys will be much stronger than those obtained from the one hundred surveys.
  5. Choose a sample: Once you have known your population, the most appropriate sampling frame, the most applicable sampling method, and the right sample size, you can put all this together to select your sample.

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Types of probability sampling methods

There are four ways through which you can perform probability sampling. We classify these into four probability sampling methods as explained below:

  • Simple random sampling: This is one of the most common probability sampling methods. It is trustworthy and helps researchers save a lot in time and resources. In simple random sampling, every member of the population is chosen randomly and every person has an equal chance of being picked to be part of the sample. For instance, if there are 1000 people living with diabetes in your area, each of the 1000 people has an equal chance of being chosen. Got a homework task that requires you to discuss simple random sampling in detail and still don’t know what to do with it? Send us a ‘do my sampling assignment’ request and we will assign the task to one of our experts.
  • Cluster sampling: This technique involves dividing the larger population into smaller sections, also known as clusters, to represent the entire population. Clusters are defined on the basis of demographic parameters like location, gender, age, income, etc. which makes it effortless for the researcher to draw effective conclusions from the study. For instance, when studying the number of people suffering from diabetes in your area, you may want to divide the data into clusters of gender and age. This way, the study will be more effective because the information will be organized into age or gender, providing more insightful results in the end. Looking to hire someone to do a cluster sampling assignment for you? Why not pay for sampling assignment writing on our website! We provide this service at the most student friendly price.
  • Systematic sampling: In systematic sampling, the individuals in the sample are selected at regular intervals in the population. For instance, if there are 1000 people living with diabetes in your area and you want to draw a sample of 100 people from this number, you will number each individual from 1 to 1000 and then choose every 10th individual to be part of the sample. This can be represented as: total population/sample size = 1000/100 = 10. To get more information about systematic sampling, collaborate with our sampling assignment help experts.
  • Stratified random sampling: In stratified sampling, the researcher divides the population into smaller groups, called strata. These groupsdo not overlap and can be organized and a sample drawn from them separately. For instance, in our diabetic patients example, we can analyze the characteristics of patients belonging to different age groups such as less than 20 years, 21 – 30 years, 31 – 40 years, 41 – 50 years, 51 – 60 years, 61 years and above, etc. Each patients from each age group (strata) can be studied to draw conclusions about the entire population. We provide exclusive help with this topic too. If you need our support, don’t hesitate to contact our sampling homework help experts.

Advantages of sampling

  • Sampling saves time and resources because we do not have to study the entire population
  • Data analysis is much easier. If a sample of 1000 people is enough to get what we want, why go studying data sets with millions of records?
  • Studies done through sampling turn out to be adequately accurate because the sample itself is a representation of the larger population and therefore exhibits the characteristics of the population.

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