## 1 Introduction  
The rapid advancement of the Generative Pre-trained Transformer (GPT) has ushered in a new era in various academic domains. Recent studies have explored the potential of chatbots like ChatGPT as an educational tool in statistics and data science, highlighting their ability to generate human-like responses, create educational content, and aid in statistical programming. For instance, [1] discusses leveraging ChatGPT's capabilities while guiding students in its responsible use. Similarly, ref. [2] delves into GPT-3.5's role in academic writing, outlining methods like \"Chunk Stylist\" and \"Research Buddy\" while balancing its benefits against potential risks. Furthermore, studies evaluating GPT models in higher education programming courses reveal their strengths and limitations in handling complex programming assessments. These insights pave the way for this study, which aims to scrutinize the effectiveness of ChatGPT and similar artificial intelligence (AI) tools in educational settings, particularly focusing on their role in teaching and learning statistics and their impact on academic integrity and editing processes. The paper by [3] presents a study that evaluates the ability of the Generative Pretrained Transformer (GPT) models to complete assessments in college-level Python programming courses. Three Python courses that employ a variety of assessments, ranging from simple multiple-choice questions to complex programming projects, were analyzed. Other research shows concern for academic integrity in the era of generative artificial intelligence by studying and reviewing 37 articles on the topic and presents approaches of the top 20 global universities to mitigate the impact of these tools on intellectual integrity and student learning [4; 5; 6]. The paper by [PERSON] [7] focuses on the impact of ChatGPT and similar AI tools on education. It discusses the challenges and opportunities presented by AI in teaching and learning, specifically in areas like reading comprehension, knowledge aggregation, and understanding genre conventions. The paper argues that AI tools like ChatGPT threaten traditional educational practices and offer unique opportunities for enhancing learning and critical thinking. The author emphasizes the need for educators to adapt and integrate AI tools into teaching strategies responsibly. Since the emergence of ChatGPT in the current world, starting in 2021 [1; 8], it is evident that it has transitioned from research labs and study centers to people's pockets through their personal devices, presenting significant challenges in approaching these new educational tools. This brings forth challenges concerning leveraging these advancements in educational studies, especially in the field of statistics [9]. The integration of chatbots like ChatGPT in mathematics education presents unique challenges compared to other subjects. While research indicates that these AI tools can enhance learning experiences, they often struggle with mathematical accuracy and conceptual understanding [10]. ChatGPT frequently produces biased or incorrect mathematical data [11], which can lead to misunderstandings due to overestimating its reliability. Additionally, studies show that ChatGPT has difficulty providing stable support in calculated reasoning processes, often resulting in confusion rather than clarity [12]. Moreover, ChatGPT performs well on non-technical questions in fields like quantitative risk management but fails in technical mathematical aspects, highlighting a significant gap in its proficiency for complex mathematical tasks [13]. Considering the information provided previously, AI in education has sparked increasing interest in its potential to enhance teaching and learning [1], as well as a lot of caution and concerns. This research aims to evaluate the use of chatbots in solving statistical problems. Beyond merely quantifying the errors produced by chatbots, the study seeks to understand the underlying causes of these errors and offer recommendations on their use to teachers and students.