Become a Probability & Statistics Master

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About Course

Learn probability and statistics from beginner to advanced with this comprehensive online course, completely free of cost! This course is taught by experienced instructor Krista King and is packed with video lessons, quizzes, and workbooks to help you master the subject. It’s perfect for students, professionals, or anyone who wants to develop a strong understanding of probability and statistics.

This course covers a wide range of topics, including:

  • Visualizing data with bar graphs, pie charts, Venn diagrams, histograms, and dot plots
  • Analyzing data with mean, median, mode, range, IQR, and box-and-whisker plots
  • Data distributions, including mean, variance, standard deviation, normal distributions, and z-scores
  • Probability, including union vs. intersection, independent and dependent events, and Bayes’ theorem
  • Discrete random variables, including binomial, Bernoulli, Poisson, and geometric random variables
  • Sampling, including types of studies, bias, sampling distribution of the sample mean or sample proportion, and confidence intervals
  • Hypothesis testing, including inferential statistics, significance levels, type I and II errors, test statistics, and p-values
  • Regression, including scatterplots, correlation coefficient, the residual, coefficient of determination, RMSE, and chi-square

This course is offered on Udemy, and it’s completely free for you to access on Theetay. Enroll today and start your journey to becoming a probability and statistics master!

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What Will You Learn?

  • Visualizing data, including bar graphs, pie charts, venn diagrams, histograms, and dot plots
  • Analyzing data, including mean, median, and mode, plus range and IQR and box-and-whisker plots
  • Data distributions, including mean, variance, and standard deviation, and normal distributions and z-scores
  • Probability, including union vs. intersection and independent and dependent events and Bayes' theorem
  • Discrete random variables, including binomial, Bernoulli, Poisson, and geometric random variables
  • Sampling, including types of studies, bias, and sampling distribution of the sample mean or sample proportion, and confidence intervals
  • Hypothesis testing, including inferential statistics, significance level, type I and II errors, test statistics, and p-values
  • Regression, including scatterplots, correlation coefficient, the residual, coefficient of determination, RMSE, and chi-square

Course Content

01 – Getting started

  • A Message from the Professor
  • 001 – What well learn in this course.mp4
    00:00
  • 002 – How to get the most out of this course.mp4
    00:00
  • 003 – Download the formula sheet.html
    00:00
  • 004 – The EVERYTHING download.html
    00:00

02 – Visualizing data

03 – Analyzing data

04 – Data distributions

05 – Probability

06 – Discrete random variables

07 – Sampling

08 – Hypothesis testing

09 – Regression

10 – Final exam and wrapup

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