[Statistics experts only]
It is Uncertainty, data, and decision class. attatched is the syllabus
The problem set is going to look like the attached files. also has to use radiant program.
I will upload the problem sets at 9:30 pm EST on Oct 23 Sunday.
And then you need to give me the answer within an hour.
This is really important for me to do well so please please if you are not willing to do or not showing up on the time please please don't do it.
please ! thank you
Session Topic(s) Lecture Notes and Deliverable(s) 1 [Course Introduction] Radiant installed «Course structure before class «Requirements and grading Lecture 1 «Introduction to Radiant (Bootcamp) 2 [Data Manipulation and Visualization] Bootcamp «Data visualizaion in Radiant «Data manipulation in Radiant «Data loading and saving in Radiant 3 [Essential Probability: Chd, 5, 6] Cectures 2,3 « Probability (Conditional, Bayes’ Rule) « Discrete random variables 4 + Continuous random variables Lecture 3 5 [Essential Statistics: Ch 2, 3] Lecture 4 « Descriptive statistics « Covariance and correlation § [Statistical Inference: Ch 7, 8, 8, 10, 11] Tecture 5 + Sampling 7 «= Population and sample Lecture 6 « Central Limit Theorem « Confidence intervals. 8 ~ Hypothesis testing Lecture 7 © Type | and Type ll errors o Significance o One-tailed and two-tailed tests 9 MIDTERM EXAM 10 + Comparing means and proportions. Lecture 8 1 + Cross-tabs Lecture 9 12 [Linear Regression: Ch 12, 13] Lecture 10 «Simple linear regression 13 + Multiple linear regression Lecture 11 + R?, p-values «Transformations 14 + Model evaluation Lecture 11 © Model fit Linearity Normality Mulicolinearity Heteroschedasticity Autocorrelation boooo