Introduction to Sampling

Question 1 

Representative samples refer to subsets of populations that seek to reflect the attributes of the larger groups accurately. The sample that Milgram used in his experiments about authority and obedience was not a representative one. The sample was self-selected through response to an advert in a newspaper. This sampling type is referred to as voluntary participation. 

Question 2 

For such a study, as mentioned in this question, the researcher must concentrate on the novices' disparities taking the course (Scheaffer, 2011). Because the course content is the same, whether done online or in-class, this would not be an essential factor. Therefore, to obtain a representative sample, I would construct a questionnaire and use stratified sampling to get a representative sample (Levy & Lemeshow, 2018). 

Question 3 

Homogeneous samples imply that all the sample items have similar attributes and traits. Therefore, there is still a need to sample to finalize the study (Levy & Lemeshow, 2018). Using homogeneous samples is important in such studies because it eliminates sampling errors. 

Question 4 

Simple random sampling: refers to a sampling methodology in which samples are selected purely based on probability, and every population member bears an equal chance of being chosen (Levy & Lemeshow, 2018). This technique is utilized when the sampling population is heterogeneous. 

Stratified sampling : Refers to a sampling method in which the entire population is divided into subpopulations (Levy & Lemeshow, 2018). It is used when the researchers seek to comprehend the existing relations between different groups. 

Disproportionate sampling : Refers to a stratified sampling approach in which the number of sampled elements in every stratum is disproportionate to the representation within the total population (Levy & Lemeshow, 2018). The sampling method is utilized when there are strata in the entire population that are minute but very significant and may not be well represented in surveys and other sampling approaches. 

Question 5 

The population is a set of similar events or items of interest. 

Population Parameter : refers to the quantities entering into the population distributions of a radon variable or statistics (Scheaffer, 2011). 

The Sampling frame is the device or the source material from which samples are drawn (Levy & Lemeshow, 2018). 

Sampling units are the building blocks of data sets. 

Samples are sets of objects or sets of individuals chosen from a specified population via defined procedures (Scheaffer, 2011). 

Sample Statistics: Are pieces of information obtained from fractions of a population. 

Question 6 

I would use a simple random sampling methodology in which samples are selected purely based on probability, and every population member bears an equal chance of being chosen. 

Question 7 

An article written by Cohn (2020) and posted on the New York Times, the opinion polls section sought to discover the degree of unity among the democrats. The article presents samples in percentiles. 

Another article posted on the USA today by Santucci (2020) conducted an opinion poll on who has a high chance of becoming the new US president between Trump and Biden. The survey uses a population sample of 1,273 registered voters in their opinion polls (Scheaffer, 2011). To determine if the polls used a representative sample, the data collection approach used must be stated. 

Question 8 

Santucci's (2020) article reports a conducted opinion poll on who has a high chance of becoming the new US president between Trump and Biden used a population sample of 1,273 registered voters in their opinion polls (Scheaffer, 2011). The sample was chosen because it represented only registered voters eligible for voting in the upcoming elections. 

Question 9 

A sampling error refers to the disparities or differences between the true population values and the obtained sample values (Scheaffer, 2011). As the sample size increases, the sampling error or margin error decreases. 

Question 10 

The advantages of probability-based sampling designs 

There are different probability sampling designs, and each has its unique merits. For instance, Cluster sampling is highly convenient and stress-free to use (Scheaffer, 2011). Simple random sampling makes extremely representative samples of a populace while samples that are greatly representative of the populace while systematic sampling makes exceedingly representative samples devoid of random number generators. 

The disadvantages of probability-based sampling designs 

The demerits of probability-based sampling designs are that they usually have a higher complexity than their counterparts, consume more time, and are expensive to perform (Scheaffer, 2011). 

The advantages of non-probability-based sampling designs 

The main merits of non-probability based sampling designs are cost-friendly and time-saving (Scheaffer, 2011). They are easy to utilize and are reliable when conducting probability sampling seems impossible. 

The disadvantages of non-probability-based sampling designs 

Some of the demerits of non-probability based sampling designs make it impossible to understand how well the sample represents the population (Scheaffer, 2011). They do not allow for the calculation of margins of error and confidence intervals. 

Question 11 

Judgemental or purposive sampling are examples of non-probability research. Based on chapter 7 of the Barbie book, scholars are often interested in deviant cases that hardy fit mainstream attitudes and behaviors (Babbie, 2016, p. 196). Babbie offers an instance of a study that seeks to gain knowledge on the o0f school motivation during the time for pep rallies. To finalize this study using probability sampling approaches, the scholars must undertake stratified sampling first. 

In purposive sampling, sample nits are selected depending on the scholar's judgment of the units' utility. When undertaking probability sampling, some sample units may not be true representatives of the entire population being studied. 

In this research study, researchers solely purpose to attain insights on the units that do not engage in the school spirit. In purposive sampling, only useful samples are selected, therefore resulting in low margin errors. 

Question 12 

For this study, I will be using samples of 25 learners aged 13-18 years. 

Learners from secondary schools will constitute the participants. The varying nits will be race, gender, and age. 

Due to the small sample size, I will select non-probability sampling and qualitative research for the research questions. Face to face interviews and quota sampling will be used. Quota sampling is selected because it offers samples in units with similar attributes (Scheaffer, 2011). 

Question 13 

A good instance pf the probability sampling approach to choose is simple random sampling. All the 150 units of the entire population would get an equal chance of being chosen for representation. Purposive sampling is the only other non-probability sampling used in this case (Scheaffer, 2011). 

If a populace is very varied, the most operative sampling technique to achieve significant outcomes would be sampling (Scheaffer, 2011). When executing stratified sampling, they should always be sub-divided into homogeneous groups before any sampling (Scheaffer, 2011). The approach raises the sample’s representativeness. 

Question 14 

Researchers in Social sciences tend to utilize probability sampling to achieve statistical inference (Scheaffer, 2011). Other than this use in non-probability sampling, scholars can easily generalize populations via probability research. With this methodology, each population unit bears an equal opportunity to be nominated for the sample. 

Question 15 

Randomization is always impossible in non-probability sampling. Social science research tends to use extensive samples, making it hard to sample the whole population randomly (Scheaffer, 2011). Instead of random sampling, the sample can be taken based on their accessibility. 

References 

Babbie, E. (2014). The basics of social research . Belmont, CA: Wadsworth https://onlinecourses.science.psu.edu/stat100/node/15/ 

Cohn, N. (2020). How United Are Democrats? A 96-0 Data Point Offers a Hint. Retrieved from: https://www.nytimes.com/2020/07/08/upshot/democrats-united-poll-election.html 

Levy, P. S., & Lemeshow, S. (2018). Sampling of populations: Methods and applications . Hoboken, N.J: Wiley. 

Santucci, J. (2020). Poll: Joe Biden leads Donald Trump by 15 points, his widest margin this year. Retrieved from: https://www.usatoday.com/story/news/politics/elections/2020/07/15/poll-biden-leads-trump-52-37-quinnipiac-poll-widest-2020-margin/5445704002/ 

Scheaffer, R. L. (2011). Elementary survey sampling . Boston, MA: Brooks/Cole.