Stat统计课程常用R语言, python和matlab等进行画图和数据统计分析. 统计和金融经济和机器学习等课程密切相关.
Important Logistics: ENSC 254 Final Project • Some general grading logistics have been posted here: https://canvas.sfu.ca/courses /83872/pages/project-logistics. Lab computer access instructions have been posted here: https://canvas.sfu.ca/courses/83872/pages/lab-logistics • The final project weighs 25% of the final marks. It includes 100 points in total, which will be scaled to 25% of the final marks. • The final …
FINAL ASSESSMENT – SUMEDH NAKOD INTRODUCTION Starbucks has over 87,000 possible drinking combinations. It is one of the most famous multinational chains of coffee houses on the planet due to its convenience, good-tasting coffee, and widespread franchises at over 30000 locations. But have you ever pondered upon what makes up our beverage? As we know, …
Introduction to statistics Models Inference Examples MTHM501- Intro to Statistics Mark Kelson, Introduction to statistics Models Inference Examples Introduction to statistics Introduction to statistics Models Inference Examples INTRODUCTION Statistics is a tool that underpins the scientific method. The truth is beyond our grasp, but knowledge grows through the gathering of evidence. Concepts are applicable almost …
2024 RMHI/ARMP Problem Set 2 Hello everyone! This is the description for the assignment, which is due on Canvas on Monday May 13, 2024 before 8:00am Melbourne time. You’ll need to submit a Word-knitted version of the completed R Markdown file found in this zip file, according to the following instructions: 1. Rename the document …
General Information for Candidates This project has 7 tasks numbered 1 through 7. The points for each task are indicated at the beginning of the task. Each task pertains to the business problem and related data files and data dictionary. An .Rmd file with some initial data work. Unless otherwise specified, each task builds upon …
COVID 19 pandemic began in March 2020, and so the airlines figured public pressu Read More »
Introduction SuperLearner and LTMLE # Install packages if (!require(“pacman”)) install.packages(“pacman”) pacman::p_load(# Tidyverse packages including dplyr and ggplot2 tidyverse, set.seed(44) SuperLearner, tidymodels, For our final lab, we will be looking at the SuperLearner library, as well as the Targeted Maximum Likelihood Estimation (TMLE) framework, with an extension to longitudinal data structures. This lab brings together a …
6-7: Sensitivity Analysis and Bounds – Solutions April 18, 2024 Sensitivity Analysis Rationale So far in our explorations of observational studies we have considered various methods of accounting for measured confounders W as well as some cases in which we can account for unmeasured confounders U (e.g. if we have measured a suitable instrumental variable). …
## Loading required package: pacman 6-6 DiD and Synthetic Control April 03, 2024 he ‘rlang’ pac # Install packages if (!require(“pacman”)) install.packages(“pacman”) # We are using a package (augsynth) that is not on CRAN, R packages on CRAN have to pass # some formal tests. Always proceed with caution if a packages is not on …
R Refresher: Notebooks, Notation and Visualization UC Berkeley Social 273M: Computational Social Science, Part B Spring 2021 Learning Objectives 2 Basic R Commands 2 Importing and Manipulating Data 5 A note on data.table vs data.frame and dplyr 9 Generating Random Numbers 9 ggplot 11 R Markdown 14 TheHeader…………………………………………. 14 Basics……………………………………………. 14 Making PDFs using R …
6-5 Instrumental Variables – Solutions March 19, 2024 Causal Graph (DAG) Review Let’s briefly review what we know about directed acyclic graphs (DAGs) or causal graphs. In this lab, we will introduce the daggity and ggdag libraries for drawing DAGs in R. Firstly, it is imperative that we keep in mind that DAGs are essentially …