Sampling Methods
Expert-defined terms from the Professional Certificate in Tourism Quantitative Research Methods course at London School of Planning and Management. Free to read, free to share, paired with a globally recognised certification pathway.
Sampling Methods #
Sampling Methods
Sampling Methods refer to the techniques used to select a subset of individuals… #
The goal of sampling methods is to ensure that the selected sample is representative of the population, allowing researchers to make accurate inferences based on the sample data.
Random Sampling #
Random Sampling
Random Sampling is a sampling method in which every member of the population has… #
This method helps eliminate bias and ensures that the sample is representative of the population. An example of random sampling is drawing names out of a hat to select participants for a study.
Stratified Sampling #
Stratified Sampling
Stratified Sampling is a sampling method in which the population is divided into… #
g., age, gender, income) and then a random sample is taken from each stratum. This method ensures that each subgroup is represented in the sample, allowing for more accurate analysis of the data.
Cluster Sampling #
Cluster Sampling
Cluster Sampling is a sampling method in which the population is divided into cl… #
All individuals within the chosen clusters are included in the sample. This method is useful when it is difficult to obtain a complete list of the population, such as in large geographical areas.
Systematic Sampling #
Systematic Sampling
Systematic Sampling is a sampling method in which every nth member of the popula… #
The starting point is randomly chosen, and then every nth element is chosen to be part of the sample. This method is simple and efficient but can introduce bias if there is a pattern in the population.
Convenience Sampling #
Convenience Sampling
Convenience Sampling is a non #
probability sampling method in which individuals who are easy to reach or readily available are selected for the sample. This method is quick and cost-effective but may not be representative of the population, as it relies on the availability of participants.
Purposive Sampling #
Purposive Sampling
Purposive Sampling is a non #
probability sampling method in which researchers select participants based on specific criteria relevant to the research study. This method is useful when researchers are looking for participants with certain characteristics or experiences that are important to the study.
Snowball Sampling #
Snowball Sampling
Snowball Sampling is a sampling method in which participants are asked to refer… #
This method is often used when the population is hard to reach or identify, such as in studies involving marginalized or hidden populations.
Quota Sampling #
Quota Sampling
Quota Sampling is a non #
probability sampling method in which researchers divide the population into subgroups based on certain characteristics and then set quotas for each subgroup. Participants are selected based on these quotas to ensure that the sample is representative of the population.
Multi #
stage Sampling
Multi #
stage Sampling is a sampling method that involves multiple stages of sampling to select participants. This method is often used in large-scale studies where it is not feasible to sample the entire population at once. Each stage of sampling helps refine the sample to ensure its representativeness.
Sampling Bias #
Sampling Bias
Sampling Bias refers to the systematic error introduced into the sample due to t… #
This bias can lead to inaccurate results and conclusions. Common types of sampling bias include selection bias, non-response bias, and measurement bias.
Selection Bias #
Selection Bias
Selection Bias occurs when certain individuals in the population are more likely… #
This bias can skew the results of a study and lead to inaccurate conclusions. Researchers must be aware of potential sources of selection bias and take steps to minimize its impact.
Non #
response Bias
Non #
response Bias occurs when individuals who choose not to participate in a study differ in important ways from those who do participate. This bias can affect the generalizability of the results and lead to flawed conclusions. Researchers must consider ways to reduce non-response bias in their studies.
Measurement Bias #
Measurement Bias
Measurement Bias occurs when the measurement instrument or process used in a stu… #
This bias can distort the results of a study and lead to incorrect conclusions. Researchers must ensure that their measurement tools are reliable and valid to minimize measurement bias.
Sampling Frame #
Sampling Frame
A Sampling Frame is a list or source from which the sample is drawn #
It is important that the sampling frame accurately represents the population of interest to ensure the validity and generalizability of the study results. Common sampling frames include directories, databases, and registries.
Population #
Population
Population refers to the entire group of individuals or units that researchers a… #
The population may be defined based on various characteristics, such as age, gender, location, or behavior. Researchers use sampling methods to select a sample from the population to study.
Sample #
Sample
A Sample is a subset of the population that is selected for study #
The sample should be representative of the population to allow researchers to make valid inferences based on the sample data. The size and composition of the sample are important considerations in research design.
Sample Size #
Sample Size
Sample Size refers to the number of individuals or units included in the sample #
The sample size should be large enough to provide sufficient statistical power to detect meaningful effects in the data. Researchers must consider factors such as the variability of the population and the desired level of precision when determining the sample size.
Sampling Error #
Sampling Error
Sampling Error is the difference between the sample estimate and the true popula… #
It is a natural part of the sampling process and is influenced by factors such as sample size and sampling method. Researchers must account for sampling error when interpreting study results.
Sampling Distribution #
Sampling Distribution
A Sampling Distribution is a theoretical distribution that represents all possib… #
It helps researchers understand the variability of sample statistics and make inferences about the population parameter. Common sampling distributions include the normal distribution and the t-distribution.
Sampling Variability #
Sampling Variability
Sampling Variability refers to the variation in sample estimates that occurs whe… #
It is influenced by factors such as sample size and sampling method. Researchers must consider sampling variability when interpreting study results to assess the reliability of their findings.
Sampling Frame Error #
Sampling Frame Error
Sampling Frame Error occurs when the sampling frame used to select the sample do… #
This error can lead to bias in the sample and affect the validity of the study results. Researchers must carefully evaluate the sampling frame to minimize sampling frame error.
Sampling Design #
Sampling Design
Sampling Design refers to the overall plan or strategy for selecting a sample fr… #
It includes decisions about the sampling method, sample size, sampling frame, and data collection procedures. A well-designed sampling plan is essential for ensuring the validity and reliability of study results.
Sampling Efficiency #
Sampling Efficiency
Sampling Efficiency refers to the ability of a sampling method to provide accura… #
Efficient sampling methods maximize the information obtained from the sample while minimizing costs and time. Researchers strive to maximize sampling efficiency in their studies.
Sampling Strategy #
Sampling Strategy
Sampling Strategy refers to the approach used to select a sample from a populati… #
The sampling strategy may vary depending on the research objectives, the characteristics of the population, and the available resources. Researchers must carefully consider their sampling strategy to ensure the validity and generalizability of the study results.
Sampling Unit #
Sampling Unit
A Sampling Unit is the individual or unit that is selected for inclusion in the… #
The sampling unit may vary depending on the research design and objectives. Common sampling units include individuals, households, organizations, and geographic areas.
Sampling Weight #
Sampling Weight
Sampling Weight is a value assigned to each sampled unit to account for the uneq… #
Sampling weights help adjust the sample data to better represent the population and improve the accuracy of estimates. Researchers must carefully calculate and apply sampling weights in their analyses.
Probability Sampling #
Probability Sampling
Probability Sampling is a sampling method in which every member of the populatio… #
This method allows researchers to calculate the probability of selection for each unit and make statistical inferences based on the sample data.
Non #
probability Sampling
Non #
probability Sampling is a sampling method in which the probability of selection for each unit is unknown or not equal. This method is often used in exploratory studies or when it is not possible to obtain a complete list of the population. Non-probability sampling methods may introduce bias into the sample.
Simple Random Sampling #
Simple Random Sampling
Simple Random Sampling is a type of random sampling in which each member of the… #
This method is straightforward and easy to implement but may not be practical for large populations. Simple random sampling is often used as the basis for other sampling methods.
Cluster Random Sampling #
Cluster Random Sampling
Cluster Random Sampling is a type of cluster sampling in which clusters are sele… #
This method is efficient for large populations and can reduce costs and time compared to other sampling methods. Cluster random sampling is useful when a complete list of the population is not available.
Systematic Random Sampling #
Systematic Random Sampling
Systematic Random Sampling is a type of systematic sampling in which every nth m… #
This method is more efficient than simple random sampling and can be easier to implement. However, systematic random sampling may introduce bias if there is a pattern in the population.
Sampling Distribution of the Sample Mean #
Sampling Distribution of the Sample Mean
The Sampling Distribution of the Sample Mean is a theoretical distribution that… #
The Central Limit Theorem states that the sampling distribution of the sample mean approaches a normal distribution as the sample size increases, regardless of the shape of the population distribution.
Sampling Distribution of the Sample Proportion #
Sampling Distribution of the Sample Proportion
The Sampling Distribution of the Sample Proportion is a theoretical distribution… #
The Central Limit Theorem states that the sampling distribution of the sample proportion approaches a normal distribution as the sample size increases, regardless of the population proportion.
Sampling Distribution of the Difference between Two Sample Means #
Sampling Distribution of the Difference between Two Sample Means
The Sampling Distribution of the Difference between Two Sample Means is a theore… #
This distribution is used to compare means between two groups and make inferences about population differences.
Sampling Distribution of the Difference between Two Sample Proportions #
Sampling Distribution of the Difference between Two Sample Proportions
The Sampling Distribution of the Difference between Two Sample Proportions is a… #
This distribution is used to compare proportions between two groups and make inferences about population differences.
Sampling Distribution of the Sample Correlation Coefficient #
Sampling Distribution of the Sample Correlation Coefficient
The Sampling Distribution of the Sample Correlation Coefficient is a theoretical… #
This distribution is used to assess the strength and direction of the relationship between two variables in the population.
Sampling Distribution of the Sample Regression Coefficient #
Sampling Distribution of the Sample Regression Coefficient
The Sampling Distribution of the Sample Regression Coefficient is a theoretical… #
This distribution is used to estimate the relationship between independent and dependent variables in the population.
Sampling Distribution of the Sample Variance #
Sampling Distribution of the Sample Variance
The Sampling Distribution of the Sample Variance is a theoretical distribution t… #
This distribution is used to estimate the variability of the population and make inferences about the population variance.
Sampling Distribution of the Sample Standard Deviation #
Sampling Distribution of the Sample Standard Deviation
The Sampling Distribution of the Sample Standard Deviation is a theoretical dist… #
This distribution is used to estimate the variability of the population and make inferences about the population standard deviation.
Sampling Distribution of the Sample Range #
Sampling Distribution of the Sample Range
The Sampling Distribution of the Sample Range is a theoretical distribution that… #
This distribution is used to estimate the spread of values in the population and make inferences about the population range.
Sampling Distribution of the Sample Median #
Sampling Distribution of the Sample Median
The Sampling Distribution of the Sample Median is a theoretical distribution tha… #
This distribution is used to estimate the central tendency of the population and make inferences about the population median.
Sampling Distribution of the Sample Mode #
Sampling Distribution of the Sample Mode
The Sampling Distribution of the Sample Mode is a theoretical distribution that… #
This distribution is used to estimate the most frequently occurring value in the population and make inferences about the population mode.
Sampling Distribution of the Sample Skewness #
Sampling Distribution of the Sample Skewness
The Sampling Distribution of the Sample Skewness is a theoretical distribution t… #
This distribution is used to assess the symmetry or asymmetry of the population distribution.
Sampling Distribution of the Sample Kurtosis #
Sampling Distribution of the Sample Kurtosis
The Sampling Distribution of the Sample Kurtosis is a theoretical distribution t… #
This distribution is used to assess the peakedness or flatness of the population distribution.
Sampling Distribution of the Sample Chi #
Square Statistic
The Sampling Distribution of the Sample Chi #
Square Statistic is a theoretical distribution that represents the distribution of chi-square statistics that could be obtained from repeated samples of a given size from a population. This distribution is used to test the independence of categorical variables in the population.
Sampling Distribution of the Sample F Statistic #
Sampling Distribution of the Sample F Statistic
The Sampling Distribution of the Sample F Statistic is a theoretical distributio… #
This distribution is used to test the equality of variances or the significance of regression coefficients in the population.
Sampling Distribution of the Sample T Statistic #
Sampling Distribution of the Sample T Statistic
The Sampling Distribution of the Sample T Statistic is a theoretical distributio… #
This distribution is used to test hypotheses about population means or regression coefficients.
Sampling Distribution of the Sample Z Statistic #
Sampling Distribution of the Sample Z Statistic
The Sampling Distribution of the Sample Z Statistic is a theoretical distributio… #
This distribution is used to test hypotheses about population proportions or means when the population standard deviation is known.
Sampling Distribution of the Sample ANOVA Statistic #
Sampling Distribution of the Sample ANOVA Statistic
The Sampling Distribution of the Sample Analysis of Variance (ANOVA) Statistic i… #
This distribution is used to test for differences in means among multiple groups in the population.
Sampling Distribution of the Sample MANOVA Statistic #
Sampling Distribution of the Sample MANOVA Statistic
The Sampling Distribution of the Sample Multivariate Analysis of Variance (MANOV… #
This distribution is used to test for differences in means across multiple dependent variables in the population.
Sampling Distribution of the Sample SEM Statistic #
Sampling Distribution of the Sample SEM Statistic
The Sampling Distribution of the Sample Structural Equation Modeling (SEM) Stati… #
This distribution is used to assess the goodness of fit of a structural equation model to the population data.
Sampling Distribution of the Sample CFA Statistic #
Sampling Distribution of the Sample CFA Statistic
The Sampling Distribution of the Sample Confirmatory Factor Analysis (CFA) Stati… #
This distribution is used to assess the goodness of fit of a confirmatory factor model to the population data.
Sampling Distribution of the Sample SEM Path Coefficients #
Sampling Distribution of the Sample SEM Path Coefficients
The Sampling Distribution of the Sample Structural Equation Modeling (SEM) Path… #
This distribution is used to estimate the relationships between latent variables in the population.
Sampling Distribution of the Sample CFA Factor Loadings #
Sampling Distribution of the Sample CFA Factor Loadings
The Sampling Distribution of the Sample Confirmatory Factor Analysis (CFA) Facto… #
This distribution is used to estimate the strength of relationships between observed and latent variables in the population.
Sampling Distribution of the Sample SEM Residuals #
Sampling Distribution of the Sample SEM Residuals
The Sampling Distribution of the Sample Structural Equation Modeling (SEM) Resid… #
This distribution is used to assess the goodness of fit of a structural equation model to the population data.
Sampling Distribution of the Sample CFA Residuals #
Sampling Distribution of the Sample CFA Residuals
The Sampling Distribution of the Sample Confirmatory Factor Analysis (CFA) Resid… #
This distribution is used to assess the goodness of fit of a confirmatory factor model to the population data.
Sampling Distribution of the Sample SEM Covariances #
Sampling Distribution of the Sample SEM Covariances
The Sampling Distribution of the Sample Structural Equation Modeling (SEM) Covar… #
This distribution is used to estimate the relationships between observed variables in the population.
Sampling Distribution of the Sample CFA Covariances #
Sampling Distribution of the Sample CFA Covariances
The Sampling Distribution of the Sample Confirmatory Factor Analysis (CFA) Covar… #
This distribution is used to estimate the relationships between observed variables in the population.
Sampling Distribution of the Sample SEM Correlations #
Sampling Distribution of the Sample SEM Correlations
The Sampling Distribution of the Sample Structural Equation Modeling (SEM) Corre… #
This distribution is used to estimate the strength and direction of relationships between observed variables in the population.
Sampling Distribution of the Sample CFA Correlations #
Sampling Distribution of the Sample CFA Correlations
The Sampling Distribution of the Sample Confirmatory Factor Analysis (CFA) #
The Sampling Distribution of the Sample Confirmatory Factor Analysis (CFA)