Length frequency distribution and mean length data are often used to estimate parameters of growth and mortality of fish stocks, as they are relatively easy to obtain from fishery-independent surveys for most fish species and can provide insights into the dynamics of fish populations, especially for data-poor or -limited fisheries. A lack of smaller size classes of fish populations may represent recruitment deficiencies, whereas a lack of larger size classes might indicate high mortality of adult individuals of fish stock. Precise and accurate estimates of population parameters are critical to ensure rational fish stock assessment and management. The performance of a survey sampling design might vary with different size structure indices, including length frequency distribution and mean length. To provide high quality length data for supporting fishery resource assessment and scientific management, the performances of the number of survey stations for estimating Enedrias fangi length frequency distribution and mean length were evaluated using computer simulations based on the original data collected from bottom trawl surveys in October 2016, and January, May, and August 2017 in the southern waters off Shandong Peninsula. The dispersion index (DI) was calculated to reflect E. fangi size composition variability within survey stations to identify the factors that influence sampling efficiency. Large DI values implied that length samples were evenly distributed among all size bins, whereas a DI close to zero indicated all observations were skewed into relatively few size bins. The sum of absolute difference (SAD) and relative estimation error (REE) were used to measure the performances (accuracy and precision) of different numbers of stations in estimating the target size structure indices. The results showed that the E. fangi length frequency distribution DI ranged from 0 to 0.91 in four seasons, whereas the DI of most stations was between 0.75 to 0.91. The number of sampling stations could be reduced so that the sampling efficiency could be improved. In general, SAD and REE showed similar trends, decreasing with sample sizes initially and then becoming stable after certain sample sizes during all four seasons, which implied that the length data estimation precision improved with an increased number of sampling stations. The optimal number of sampling stations varied with target indices. The optimal sample size was 20 stations for estimating length frequency distribution and 30 stations for estimating mean length. This study identified the accepted optimal sample sizes to estimate length frequency distribution and mean length and could provide a technical reference for fishery-independent surveys to estimate the size structure index.