Highly Qualified Statistics Tutor Required

Hi there, I am a student at the University of Melbourne. Pursuing a Master of Data Science. I need to hire a tutor from the preferably the same field or have a qualification in statistics (PhD preferred). I just need tuition for 3 hours and you will be paid really generously. Further details can be discussed in the chat section. Keep in mind highly qualified and must have knowledge of these domains. Cheers! Module1: Introduction Module2: Linear Algebra Attachment Module2: Linear Algebra Module3: Random Vectors Attachment Module3: Random Vectors Module4.1: Full Rank Linear Models Attachment Module4.1: Full Rank Linear Models Module4.2: Full Rank Linear Models Attachment Module4.2: Full Rank Linear Models Module4.3: Full Rank Linear Models Attachment Module4.3: Full Rank Linear Models Module4.4: Full Rank Linear Models Attachment Module4.4: Full Rank Linear Models Module4.5: Full Rank Linear Models Attachment Module4.5: Full Rank Linear Models Module4.6: Full Rank Linear Models Attachment Module4.6: Full Rank Linear Models Module5.1: Hypothesis Testing Attachment Module5.1: Hypothesis Testing Module5.2: Hypothesis Testing Attachment Module5.2: Hypothesis Testing Module5.3: Hypothesis Testing Attachment Module5.3: Hypothesis Testing Module5.4: Hypothesis Testing Attachment Module5.4: Hypothesis Testing Module5.5: Hypothesis Testing Attachment Module5.5: Hypothesis Testing Module5.6: Hypothesis Testing Attachment Module5.6: Hypothesis Testing Module 6.1: One Way Classification, Reparameterization Attachment Module 6.1: One Way Classification, Reparameterization Module 6.2: Estimability, Testability, Two factor Attachment Module 6.2: Estimability, Testability, Two factor Module6.3: Interaction, ANCOVA Attachment Module6.3: Interaction, ANCOVA Module6.4: Causality, Design Principles, CRD Attachment Module6.4: Causality, Design Principles, CRD Module7.1: Binomial Regression Attachment Module7.1: Binomial Regression Module7.2: Maximum Likelihood Attachment Module7.2: Maximum Likelihood Module7.3 Inference, Likelihood Ratio Test Attachment Module7.3 Inference, Likelihood Ratio Test Module8.1: Exponential family, GLM Attachment Module8.1: Exponential family, GLM Module8.2: Weighted Least Squares Attachment Module8.2: Weighted Least Squares Module8.3: Inference in GLM Attachment Module8.3: Inference in GLM Module8.4: GLM Diagnostics Attachment Module8.4: GLM Diagnostics Module9.1: Multinomial and Ordinal Data Attachment Module9.1: Multinomial and Ordinal Data Module9.2: Contingency Table Attachment Module9.2: Contingency Table Module10.1: Inversion sampling Attachment Module10.1: Inversion sampling Module10.2: Rejection Sampling Attachment Module10.2: Rejection Sampling Module10.3: MCMC Attachment Module10.3: MCMC Module10.4: Gibbs [login to view URL] Attachment Module10.4: Gibbs [login to view URL] Module11.1-2: Intro to Bayesian Inference, Conjugate prior Attachment Module11.1-2: Intro to Bayesian Inference, Conjugate prior Module11.3: Approximate inference using MCMC Attachment Module11.3: Approximate inference using MCMC Module12.1: PCA Attachment Module12.1: PCA Module12.2: K-mean clustering Attachment Module12.2: K-mean clustering