Iniobong Stephen Statistics / Data Analysis Tutor
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Passionate Data Science & Statistics Tutor | Helping You Master Data with Confidence

Are you struggling with statistics or data science concepts? Do you want to improve your analytical skills and apply data-driven insights to real-world problems? I’m here to help!

As a highly experienced tutor, I specialize in breaking down complex topics into simple, easy-to-understand lessons. With a strong background in Statistics and Data Science, I teach students of all levels—from beginners to advanced learners—helping them grasp key concepts like:

✅ Descriptive & Inferential Statistics – Mean, variance, hypothesis testing, confidence intervals
✅ Probability & Distributions – Normal, binomial, Poisson, and more
✅ Regression & Machine Learning – Linear/logistic regression, decision trees, neural networks
✅ Data Wrangling & Visualization – Pandas, NumPy, Matplotlib, Seaborn, Power BI
✅ Python, R, & SQL for Data Science – Hands-on coding for real-world applications

I provide personalized lessons, hands-on coding exercises, and real-world examples to ensure you truly understand the material. Whether you're preparing for exams, certifications, research projects, or career advancement, I’ll guide you every step of the way.

Let’s unlock your potential and make Statistic easy, practical, and enjoyable! Book a session today and start mastering data with confidence. 🚀

Subjects

  • R programming language Beginner-Intermediate

  • Statistics and data analysis Beginner-Expert

Experience

  • Statistics (Mar, 2024–Present) at 1 year experince online teaching on preply
    As a Statistics Tutor, my roles and responsibilities include:

    Teaching & Instruction
    Explain statistical concepts in a clear, engaging, and simplified manner.
    Develop customized lesson plans tailored to each student’s learning style and goals.
    Use real-life examples and applications to make statistics more relatable.
    Guide students through problem-solving techniques and data analysis.
    Student Support & Engagement
    Assess students’ strengths and areas for improvement.
    Provide constructive feedback and encouragement to boost confidence.
    Help students prepare for exams, assignments, and research projects.
    Use interactive teaching methods, including software (SPSS, R, Python, Excel, etc.).
    Practical Application & Technology
    Teach students how to use statistical tools for data analysis.
    Assist with hypothesis testing, regression analysis, ANOVA, probability distributions, etc.
    Support students in understanding research methods and interpreting results.
    Mentorship & Motivation
    Inspire students by sharing practical applications of statistics in various fields.
    Foster critical thinking and problem-solving skills.
    Help struggling students overcome math anxiety and build confidence.
  • Data science (Aug, 2021–Present) at Alliant Group of Schools
    As a Data Science Teacher, my roles and responsibilities include:

    Teaching & Instruction
    Deliver clear and engaging lessons on data science concepts, including data wrangling, visualization, machine learning, and statistical modeling.
    Design structured lesson plans that cater to different learning styles and student levels.
    Use real-world case studies and datasets to demonstrate practical applications.
    Explain programming concepts in Python, R, and SQL for data analysis.
    Student Support & Engagement
    Assess students’ strengths and weaknesses, adapting lessons to meet their needs.
    Provide hands-on coding exercises, projects, and assignments.
    Offer guidance on data-driven decision-making and problem-solving.
    Encourage active learning through discussions, coding challenges, and group projects.
    Practical Application & Technology
    Teach the use of essential tools like Pandas, NumPy, Matplotlib, Scikit-learn, TensorFlow, and Power BI.
    Guide students in using cloud platforms like Google Colab, AWS, or Azure.
    Explain machine learning algorithms, AI concepts, and model evaluation techniques.
    Introduce students to big data concepts, databases, and data engineering fundamentals.
    Mentorship & Career Guidance
    Help students understand the real-world applications of data science in industries like healthcare, finance, and marketing.
    Assist with portfolio building, capstone projects, and resume preparation.
    Provide career advice on roles such as data analyst, data engineer, and machine learning engineer.
    Foster curiosity, creativity, and problem-solving skills in students.

Education

  • Statistics (Oct, 2010–Mar, 2013) from Federal polytechnic nekede, Owerri

Fee details

    ₦7,000–25,000/hour (US$5.10–18.23/hour)

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