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State Plan AR FY26 - Original Submission Page of 51 112 3. Accuracy: The ARIES system undergoes regular quality assurance and validation checks to maintain the accuracy of participant records. Eligibility staff update records promptly upon case changes to ensure data integrity. 4. Completeness: The database includes all enrolled participants for the specified Federal Fiscal Year, encompassing demographic, eligibility, and participation information necessary for sampling. 5. Components: The data components used for sampling include unique participant identifiers (such as SSN or ARIES ID), enrollment status, participation status, and work requirement codes. 6. Location: The source data resides within the Arkansas Department of Human Services’ secure ARIES database environment. 7. Form: Participant data is stored in a structured digital format within ARIES, allowing for efficient querying, filtering, and extraction of records. 8. Frequency of Updates: Data in ARIES is updated continuously as eligibility and participation information changes occur, with snapshots taken monthly to provide stable datasets for sampling purposes. 9. Structure: The participant data is organized in relational tables within ARIES, enabling extraction of randomized samples using data management tools with criteria-based queries. ________________________________________ Random Sampling Procedure: • Step 1: Obtain the latest snapshot of the participant dataset as of the target sampling date, ensuring the dataset reflects all active participants within the sampling frame. • Step 2: Define the sampling frame parameters, such as participant status (e.g., currently active, enrolled within a certain period) and any exclusion criteria (e.g., exempt participants). • Step 3: Use a statistical software or data management tool to generate a random selection of participants from the sampling frame. The tool will utilize a random number generator to select participants without bias. • Step 4: Validate the random sample to confirm that it meets sample size requirements and represents the overall population. • Step 5: Document the sampling methodology, including data source, extraction date, sample size, and selection criteria, to maintain audit readiness and transparency. What is the method of sample selection used for the random sample? The random sample is selected using a simple random sampling method. This approach ensures that each eligible participant within the defined sampling frame has an equal probability of being chosen. The process employs a computerized random number generator or statistical software to generate unbiased, random selections from the complete and updated participant dataset. This method eliminates selection bias and supports the representativeness of the sample for program evaluation or monitoring purposes. What are the procedures for estimating caseload size for the random sample? • Define the Population: Identify the total population of SNAP E&T participants eligible for sampling. This includes all active participants within the selected time frame who meet the inclusion criteria (e.g., non-exempt work registrants). • Calculate Initial Sample Size: Use a standard sample size formula or statistical software to calculate the initial sample size based on the