Property group	Property Name	Description	Misc.	Note
Selection options	Sampling method	Select sampling method.	Required	Random Sampling, Systematic Sampling, Stratified Sampling, From the beginning, Stratified Sampling (Equal Partition)
Selection options	Selection status	Specify whether you want to use or exclude the extracted data.	Required	Select, Exclusion
Selection options	Discrete Variable	Select the discrete variable to be used as the basis for stratified sampling.
Sample size	Sample size method	Specify the method for determining the sample size.	Required	Percentage, Count.
Sample size	Sample size (percentage)	Set the Percentage of samples for sampling. If the calculated sample count is not an integer, it is roundest to integer		real numbers from 0 to 100
Sample size	Sample size (Count)	Set the number(count) of samples for sampling		integer
NOTE: Description of the sampling method. Random Extraction: Extract data randomly using tools such as random number tables. Hierarchy Extraction: Order every member of the population, extract one sample randomly, and then extract subsequent samples at fixed intervals. (Note: Only up to 50% of the total data can be sampled. Additionally, if the calculated sampling interval is not an integer, it is rounded to the nearest integer.) Stratified Sampling: Dividing the population into homogeneous subgroups and then randomly sampling from these subgroups based on their sizes.	NOTE: Description of the sampling method. Random Extraction: Extract data randomly using tools such as random number tables. Hierarchy Extraction: Order every member of the population, extract one sample randomly, and then extract subsequent samples at fixed intervals. (Note: Only up to 50% of the total data can be sampled. Additionally, if the calculated sampling interval is not an integer, it is rounded to the nearest integer.) Stratified Sampling: Dividing the population into homogeneous subgroups and then randomly sampling from these subgroups based on their sizes.	NOTE: Description of the sampling method. Random Extraction: Extract data randomly using tools such as random number tables. Hierarchy Extraction: Order every member of the population, extract one sample randomly, and then extract subsequent samples at fixed intervals. (Note: Only up to 50% of the total data can be sampled. Additionally, if the calculated sampling interval is not an integer, it is rounded to the nearest integer.) Stratified Sampling: Dividing the population into homogeneous subgroups and then randomly sampling from these subgroups based on their sizes.	NOTE: Description of the sampling method. Random Extraction: Extract data randomly using tools such as random number tables. Hierarchy Extraction: Order every member of the population, extract one sample randomly, and then extract subsequent samples at fixed intervals. (Note: Only up to 50% of the total data can be sampled. Additionally, if the calculated sampling interval is not an integer, it is rounded to the nearest integer.) Stratified Sampling: Dividing the population into homogeneous subgroups and then randomly sampling from these subgroups based on their sizes.	NOTE: Description of the sampling method. Random Extraction: Extract data randomly using tools such as random number tables. Hierarchy Extraction: Order every member of the population, extract one sample randomly, and then extract subsequent samples at fixed intervals. (Note: Only up to 50% of the total data can be sampled. Additionally, if the calculated sampling interval is not an integer, it is rounded to the nearest integer.) Stratified Sampling: Dividing the population into homogeneous subgroups and then randomly sampling from these subgroups based on their sizes.