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Artificial Intelligence Basics
Published in Subasish Das, Artificial Intelligence in Highway Safety, 2023
Simple Random Sampling: Simple random sampling ensures a sampling technique wherein each unit of the population has an equal likelihood of being picked. This method has two categories: with and without replacement. Simple random sampling with substitution allows the return of the element drawn from the population before the next draw. Repeat selection is not allowed by the technique without replacement. Unbiased estimates of the population mean with an unbiased estimate of variability, used to evaluate the result’s reliability, are offered by simple random sampling. n distinct units are chosen from the N units in the population so that each possible arrangement of n units is equally likely to be the sample chosen in simple random sampling without replacement. Figure 19 illustrates a sampling technique used in simple random sampling. It shows that from a population of 25 units, 8 random units are picked.
Communication
Published in Walter DeGrange, Lucia Darrow, Field Guide to Compelling Analytics, 2022
When selecting participants for a focus group, it is important to consider who will be most likely to contribute useful information. A few different ways to select participants are: Random sampling: In this method, everyone in the population has an equal chance of being selected.Stratified sampling: In this method, the population is divided into groups (or strata) and people are selected from each group at random.Cluster sampling: In this method, clusters of people are randomly selected, and then individual participants are chosen from within the clusters.Quota sampling: In this method, a certain number of participants from specific groups are chosen.Convenience sampling: In this method, participants are selected based on convenience (for example, people who are available at a specific time and place).
STATISTICAL CONTROL OF PROCESSES
Published in Ronald J. Cottman, Total Engineering Quality Management, 2020
Sampling is the statistical procedure of removing a carefully selected number of items from a population and then making a decision about the population based on the information gained from the sample data taken. In taking samples, the items should be selected randomly to ensure that only inherent variation is present. That is, every cause of variation must act on individual items selected in the exact same manner. When a sample is correctly selected, the total population is represented by the sample data. The population can then be accepted or rejected on the strength of the sample taken. Sampling done randomly contains all of the characteristics of its underlying population and variations in the process will begin to emerge. Figure 7 in Chapter 8 is a display of sample voltage readings conducted on one pin of a development ramp generator printed circuit card. The samples shown in the example were taken over a period of one full shift and are a representative example of one manner of sampling. The time period over which samples are taken is directly proportional to the accuracy required.
Understanding household attitudes to water conservation in Saudi Arabia: towards sustainable communities
Published in International Journal of Water Resources Development, 2023
Abdulaziz I. Almulhim, Ismaila Rimi Abubakar
A multi-stage sampling approach combining stratified and simple random sampling was adopted to account for the city’s social groups and housing types. Stratified random sampling is a probability sampling method that entails dividing the population into subgroups and then selecting a sample from each subgroup. The study area is officially categorized into central, western, eastern, northern and southern sectors, which differ in land uses, population density and housing types. One neighbourhood was randomly selected from each sector, except for the central sector, where two neighbourhoods were selected because of its large size and high proportion of expatriate workers. The selected neighbourhoods were Alrawdhah, Alaskan, Badr, Aljalawiyah, Mubarakiyahh and Alommal (Figure 2). In the second stage of sampling, a random sampling technique was used to select two schools from each of the six neighbourhoods, depending on the number and size of schools in the area. This approach ensures the optimal representation of the study population.
Built environment transformation in Nigeria: the effects of a regenerative framework
Published in Journal of Asian Architecture and Building Engineering, 2023
Oluwagbemiga Paul Agboola, Badr Saad Alotaibi, Yakubu Aminu Dodo, Mohammed Awad Abuhussain, Maher Abuhussain
For satisfactory data gathering and removal of bias, stratified random sampling was adopted. Stratified sampling involves dividing the population into homogeneous subgroups (strata) based on certain characteristics. In this case, the strata have been determined by specific factors related to the built environment or location within southwestern Nigeria. By sampling within each stratum, we ensure that different segments of the population are represented. This sampling technique allows for a more representative and accurate analysis of the different predictors, impacts of climate change, and regenerative factors within the built environment in southwestern Nigeria. According to Creswell (2012), using stratified sampling in conjunction with probability sampling is the most effective technique for minimising bias. A total of 314 survey questionnaires were distributed, and 235 were retrieved and deemed suitable for analysis. To calculate the response rate, we divided the number of retrieved questionnaires by the number of distributed questionnaires and then multiplied by 100 to get the percentage. Therefore, the response rate stood at approximately 74.84%, which was a justifiable percentage (Moser and Kalton 1971). According to the literature, when employing the questionnaire method, a response rate exceeding 30% is commonly regarded as a satisfactory and acceptable level (Crimp and Wright 1995).
Optimize the online shopping title of men’s plain-color shirts in e-commerce based on Kansei Engineering
Published in Journal of Global Fashion Marketing, 2023
Simple random sampling is probability sampling, that is, each member of the population has an equal chance to be selected (Creswell, 2017). A 5-point Likert scale questionnaire is a common instrument used in simple random sampling. The online questionnaire is a safe and effective form of the questionnaire under special circumstances. Longitudinal and cross-sectional studies are two ways of collection for sampling. In longitudinal studies, data are collected repeatedly from the same sample at different times; in cross-sectional studies, data are collected from the population at specific time points. Therefore, this study will use a 5-point Likert scale web questionnaire, cross-sectional study to conduct a simple random sampling focus on consumers aged 20-35 who have purchased men’s plain-color shirts during online shopping in the past year online.