Statistics · Columbia University
Linear Regression, Probability, Theoretical Model Testing.
I was able to see and learn about the many different ways probability is being applied in the research sphere. I think it is helpful in shaping my idea of what research can look like.
Fisher Information, Bayer's rule, Generalized Likelihood Ratio, Hypothesis testing
Histograms, normal curve, regression, correlation, double-blind randomized controlled experiments, etc.
Very Unclear, the content itself is already very hard, the professor made it even harder to understand
how to read histograms, what a normal curve is and how it works, z and t tables are and regression lines mostly statistics to help understand how stats and graphs seen in everyday life actually work
poor structure of the course, poor teaching of the course
I learned about statistics, probability, and things relevant to the normal curve.
Just do it. Everything is great! 1 Columbia University: Arts & Sciences Spring 2022 Course: STATGU4204_003_2022_1-STATISTICALINFERENCE : STATGU4204_003_2022_1 - STATISTICAL INFERENCE Instructor: Victor De la Pena
Relative frequency hisograms, standard deviation, normal distribution, regression, confidence intervals, and more. Overall useful for basics of stats