This study addressed whether gender, social desirability, statistics levels, and statistics self-efficacy can significantly predict variation in statistics anxiety at the graduate level. Statistics anxiety undermines performance throughout academia and reduces employment opportunities that require skills in statistics. Previous studies have indicated inconsistencies related to the quality and type of instruments used to assess the predictors of statistics anxiety and the significance of social desirable responses. The research methodology used in the study was nonexperimental with a convenience sample of graduate degree holding and enrolled graduate level participants. The research population consisted of individuals throughout the United States who had completed or were enrolled in a graduate level statistics or research methods course. Data were collected across 3 months through a contract with Qualtrics. The survey included demographic information (i.e., gender, levels of statistics), 16 social desirability items, 26 statics self-efficacy items, and 23 statistics anxiety items. Six surveys were removed from the initial 225 surveys because the participants failed to fully meet inclusion criteria and/or because items were missed. SPSS Statistics 27 and JMP 16 generated descriptive statistics for a sample size of N = 219. Data were generated using standard ordinary least square multiple regressions and penalized regression. The adaptive elastic net procedures (using penalized regression) indicated social desirability significantly predicted statistics anxiety. The model accounted for 8.6% of the variance in statistics anxiety using adaptive elastic net penalized regression. A moderation analysis of the data revealed neither gender, statistics level (completed and enrolled in), nor statistics self-efficacy significantly changed the relationship between social desirability and statistics anxiety. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://bibliotheek.ehb.be:2222/en-US/products/dissertations/individuals.shtml.]