Intro to Statistics | Making Decisions Based on Data
Details
Statistics is about extracting meaning from data. In this class, we will introduce techniques for visualizing relationships in data and systematic techniques for understanding the relationships using mathematics.
This course will cover visualization, probability, regression and other topics that will help you learn the basic methods of understanding data with statistics.
This course does not require any previous knowledge of statistics. Basic familiarity with algebra such as knowing how to compute the mean, median and mode of a set of numbers will be helpful.
See the Technology Requirements for using Udacity here https://www.udacity.com/tech-requirements.
Outline
Seeing relationships in data and predicting based on them; Simpson's paradox
Lesson 2: ProbabilityProbability; Bayes Rule; Correlation vs. Causation
Lesson 3: EstimationMaximum Likelihood Estimation; Mean, Median, Mode; Standard Deviation, Variance
Lesson 4: Outliers and Normal DistributionOutliers, Quartiles; Binomial Distribution; Central Limit Theorem; Manipulating Normal Distribution
Lesson 5: InferenceConfidence intervals; Hypothesis Testing
Lesson 6: RegressionLinear regression; correlation
Lesson 7: Final ExamSpeaker/s
Sebastian Thrun is a Research Professor of Computer Science at Stanford University, a Google Fellow, a member of the National Academy of Engineering and the German Academy of Sciences. Thrun is best known for his research in robotics and machine learning, specifically his work with self-driving cars.
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