Sampling and Sampling distributions

Sampling is a technique to draw samples from a population, that is, Sampling is a process. The sampling distribution is a probability distribution of a statistic (such as mean, variance, proportion, etc.). This category contains posts about sampling and sampling distribution.

Best Sampling Quiz – 4

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The sampling Quiz in this post covers the MCQs related to Sampling and Sampling Distributions, Probability Sampling and Non-Probability Sampling, Mean and Standard Deviation of Sample, Sample size, Sampling error, Sample bias, Sample Selection, etc.

Sampling Quiz is about Basics of Sampling and Sampling Distributions. It will help you to understand the basic concepts related to sampling methods and sampling distributions. This test will also help you to prepare yourself for different exams related to education or jobs.

1. Sampling-based on equal probability is called

 
 
 
 

2. The probability distribution of a statistic is called

 
 
 
 

3. A data professional is analyzing data about a population of aspen trees. They take repeated random samples of 10 trees from the population and compute the mean height for each sample. Which of the following statements best describes the sampling distribution of the mean?

 
 
 
 

4. To make a voter list in Pakistan we need

 
 
 
 

5. If we obtain a point estimate $\overline{X}$ for a population mean $\mu$, the difference between $\overline{X}$ and $\mu$ is called

 
 
 
 

6. A sample is a subset of

 
 
 
 

7. What is a standard error?

 
 
 
 

8. In sampling with replacement, an element can be chosen

 
 
 
 

9. Any measure of the population is called

 
 
 
 

10. The difference between a statistic and the parameter is called

 
 
 
 

11. A population about which we want to get some information is called

 
 
 
 

12. A clothing manufacturer wants to learn more about why their consumers have purchased the brand’s products. How should this manufacturer conduct their survey?

 
 
 
 

13. Any calculation on the sample data is called

 
 
 
 

14. A distribution formed by all possible values of a statistic is called

 
 
 
 

15. A high school principal is estimating the total number of students that will attend an upcoming event. She assumes that the older students are unlikely to attend and decides to only survey the first-year students. What issue will the principal face when calculating her estimation?

 
 
 
 

16. The study of population is called

 
 
 
 

17. A company is trying to learn more about their customer base. They would like to survey to understand why their customers chose their brand. How should the company survey its customers?

 
 
 
 

18. The standard deviation of the sampling distribution of a statistic is called

 
 
 
 

19. A list of all the units of the population is called

 
 
 
 

20. In probability sampling, the probability of selecting an item from the population is known and is

 
 
 
 

Question 1 of 20

Online Sampling Quiz with Answers

  • A sample is a subset of
  • A list of all the units of the population is called
  • Any calculation on the sample data is called
  • Any measure of the population is called
  • The difference between a statistic and the parameter is called
  • The probability distribution of a statistic is called
  • The standard deviation of the sampling distribution of a statistic is called
  • If we obtain a point estimate $\overline{X}$ for a population mean $\mu$, the difference between $\overline{X}$ and $\mu$ is called
  • A distribution formed by all possible values of a statistic is called
  • In probability sampling, the probability of selecting an item from the population is known and is
  • A population about which we want to get some information is called
  • The study of population is called
  • To make a voter list in Pakistan we need
  • Sampling-based on equal probability is called
  • In sampling with replacement, an element can be chosen
  • A company is trying to learn more about their customer base. They would like to survey to understand why their customers chose their brand. How should the company survey its customers?
  • A high school principal is estimating the total number of students that will attend an upcoming event. She assumes that the older students are unlikely to attend and decides to only survey the first-year students. What issue will the principal face when calculating her estimation?
  • A clothing manufacturer wants to learn more about why their consumers have purchased the brand’s products. How should this manufacturer conduct their survey?
  • What is a standard error?
  • A data professional is analyzing data about a population of aspen trees. They take repeated random samples of 10 trees from the population and compute the mean height for each sample. Which of the following statements best describes the sampling distribution of the mean?
Sampling and Sampling Distribution Quiz

The sampling Quiz is about the Basics of Sampling and Sampling Distributions. It will help you to understand the basic concepts related to sampling methods and sampling distributions. This test will also help you to prepare yourself for different exams related to education or jobs.

Computer MCQs

R and Data Analysis

Probability and Non-Probability Sampling

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The fundamental methods of Probability and non-probability sampling are used for selecting a sample from a population in research studies. They differ in how they approach the selection process and the resulting generalizability of the findings. The non-probability sampling methods are valuable for initial research stages or specific situations, but for strong statistical inferences and generalizability, probability sampling is preferred.

In probability sampling, each unit of the population has a known (non-zero) probability of being included in the sample, and samples are selected randomly by using some random selection method. That’s why probability sampling may also be called random sampling. In probability sampling, the reliability of the estimates can be determined. In probability sampling, samples are selected without any interest. The advantage of probability sampling is that it provides a valid estimate of sampling error. Probability sampling is widely used in various areas such as industry, agriculture, business sciences, etc.

Types of Probability Sampling

Important types of probability sampling are

  • Simple Random Sampling
  • Stratified Random Sampling
  • Systematic Sampling
  • Cluster Sampling
Sample and Sampling

These sampling methods are capable of

  • Generalizability: Results can be statistically projected to the entire population.
  • Accuracy: Reduces bias, ensuring a representative sample.
  • Statistical Analysis: Allows for confidence intervals and hypothesis testing.

and are used in

  • Opinion polls
  • Market research
  • Government surveys (e.g., census)
  • Medical trials

Types of Non-Probability Sampling

In this sampling technique, samples are selected by personal judgment; due to this personal judgment in the selection of the sample, bias may be introduced, which makes the result unrepresentative. This sampling technique may also be called non-random sampling. The disadvantage of non-probability is that the reliability of the estimates cannot be determined.

The Non-Probability Samplings are:

  • Purposive sampling
  • Quota sampling
  • Judgment sampling
  • Snowball sampling
  • Convenience sampling

These sampling methods are:

  • Cost & Time Efficiency: Quicker and cheaper than probability sampling.
  • Exploratory Research: Useful for preliminary insights.
  • Hard-to-Reach Populations: Helps study niche or hidden groups.

and are widely used in

  • Pilot studies
  • Qualitative research (e.g., interviews)
  • Case studies
  • Social media surveys

Differences between Probability and Non-Probability Sampling

The difference between these two is that non-probability sampling does not involve random selection of objects, while in probability sampling, objects are selected by using some random selection method. In other words, it means that non-probability samples aren’t representative of the population, but it is not necessary. However, it may mean that non-probability samples cannot depend upon the rationale of probability theory.

In general, researchers may prefer probabilistic or random sampling methods over non-probabilistic sampling methods and consider them to be more accurate and rigorous.  However, in applied social sciences, for researchers, there may be circumstances where it is not possible to obtain sampling using some probability sampling methods. Even practical or theoretical, it may not be sensible to do random sampling. Therefore, a wide range of non-probability sampling methods may be considered in these circumstances.

FeatureProbability SamplingNon-Probability Sampling
SelectionRandomNon-random
BiasLowHigh
GeneralizabilityHigh (if done correctly)Low
Cost & EffortHighLow
Best ForQuantitative researchQualitative/exploratory research
Probability and Non-Probability Sampling

The choice between probability and non-probability sampling depends on the research question, resources available, and the desired level of generalizability.

  • Use probability sampling when the generalizability of findings to the population is crucial, and resources allow for random selection.
  • Use non-probability sampling when: You need a quick and easy way to gather initial insights, explore a topic, or a complete sampling frame is unavailable. However, be cautious about generalizing the results.
ApplicationNon-Probability SamplingProbability Sampling
GoalInitial insights, specific situationsGeneralizable Finding
Selection MethodConvenience, judgement basedRandom
GeneralizabilityLimitedHigh
ExamplePilot studies, focus groups, market research, case studiesPublic opinion polls, medical research

In summary, use probability sampling when you need statistically valid, generalizable results. Use non-probability sampling when quick, cost-effective insights are needed, or when studying specific groups.

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Read More about Sampling Basics

R and Data Analysis

Test Preparation MCQs

Sampling Basics and Objectives (2021)

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In this article, we will discuss the Sampling Basics. It is often required to collect information from the data. These two methods are used for collecting the required information.

  • Complete information
  • Sampling

Complete Information

This method collects the required information from every individual in the population. This method is used when it is difficult to draw some conclusion (inference) about the population based on sample information. This method is costly and time-consuming. This method of getting data is also called Complete Enumeration or Population Census.

Sampling Basics

What is Sampling?

Sampling is the most common and widely used method of collecting information. Instead of studying the whole population only a small part of the population is selected and studied and the result is applied to the whole population. For example, a cotton dealer picked up a small quantity of cotton from the different bales to know the quality of the cotton.

Sampling and Sampling Distribution

Purpose or objective of sampling

Two basic purposes of sampling are

  1. To obtain the maximum information about the population without examining every unit of the population.
  2. To find the reliability of the estimates derived from the sample, which can be done by computing the standard error of the statistic.

Advantages of sampling over Complete Enumeration

  1. It is a much cheaper method to collect the required information from the sample as compared to complete enumeration as fewer units are studied in the sample rather than the population.
  2. From a sample, the data can be collected more quickly and greatly save time.
  3. Planning for sample surveys can be done more carefully and easily as compared to complete enumeration.
  4. Sampling is the only available method of collecting the required information when the population object/ subject or individual in the population is destructive.
  5. Sampling is the only available method of collecting the required information when the population is infinite or large enough.
  6. The most important advantage of sampling is that it provides the reliability of the estimates.
  7. Sampling is extensively used to obtain some of the census information.
Sampling Basics and Objectives

This is all about Sampling Basics.

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For further reading visit: 

Sampling Theory and Reasons to Sample
Sampling Basics

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