ACT Math & Statistics that’s practical & fun

Hello, I'm Deeksha Khurana, a math enthusiast with a passion for teaching! With a Masters in Statistics , I specialize in tutoring Data Science and Statistics to school-level students. My teaching philosophy revolves around making complex math concepts understandable and engaging for students. I believe in creating a supportive learning environment where students feel comfortable asking questions and exploring new ideas. By incorporating real-life examples and interactive activities, I aim to enhance student engagement and foster a deeper understanding of the subject. Two main statistical methods used in data analysis are descriptive statistics and inferential statistics. Descriptive statistics summarize data from a sample, while inferential statistics draw conclusions from data that are subject to random variation. Also I have worked with SPSS and Excel for Data Analysis. I have attended many workshops related to data analysis. I was also a part of research project in my masters in which we have analyzed the data of a hospital related hypertension patients using STATA software and little bit of software R. Join me on this learning journey, and together we can conquer the world of numbers!

As an GCSE Math and Statistics tutor for school students, my tutoring methodology focuses on interactive and problem-solving approaches. I believe in being concept-focused and detail-oriented, ensuring that students have a strong understanding of the material. My teaching style is structured and systematic, providing a clear framework for learning. I use demonstrative methods to help students visualize and understand mathematical concepts. Additionally, I specialize in teaching data science using real-world datasets and visualization tools, offering practical projects that encourage analysis of complex data. Flipped classroom: Students learn content before class, such as through homework or pre-reading, and then use class time for discussions and activities. Inquiry-based learning: Students are encouraged to ask questions, investigate, and explore topics in depth. Project-based learning: Students learn data science practices based on real-world problems and data. Teach statistical thinking: The goal is to help students develop a more global perspective on data and distributions. Differentiation: The student is at the center of all decision making, with the aim of maximizing each student's capacity. Foster active learning: Link the power of social media use with active learning methods to improve engagement and learning outcomes. Use classroom data: Students love activities that apply directly to them. Use school data: Gathering school data can be a great way to teach statistics. Use social media: Use social media to teach statistics. Use observations from outside: Use observations from outside to teach statistics. Use interesting studies: Use interesting studies to teach statistics.