This blog build GD algorithm via Julia programming language

Abstract This study explored school- and teacher-level factors associated with a higher probability of teachers’ implementation of student-centered instructional practices. These practices include adaptive instruction and active teaching strategies that support learning enhanced by information communication technology (ICT), collaborative small-group learning, and project-based learning.

This tutorial aims to explore various types of tools of visualizing the process data.

Abstract Posterior Predictive Model Checking (PPMC) is frequently used for model fit evaluation in Bayesian Confirmatory Factor Analysis (BCFA). In standard PPMC procedures, model misfit is quantified by the location of a ML-based estimate to the predictive distribution of a statistic for a model.

A introduction about gt package is here knitr::opts_chunk$set(echo = TRUE, warning = FALSE, message = FALSE, fig.align = "default", eval = TRUE) library(gt) suppressMessages(library(tidyverse)) Basics of gt A basic gt table can be created as so

Last night, I read the 1st chapter of Statistical Rethinking: A Bayesian Course with Examples in R and Stan from Richard McElreath. I found this is nice book to share with my friends.

R language could be easily used as a bash script using Rscript *.R. system() is a R base function which could run command line within R. Below is a simple example which allows to automate create a new blog post: (1) Ask users to type in filename, title and language (2) Create a new markdown file in specific directory (i.

A brief introduction of using Network Model to visualize latent attributes' hierarchy of Diagnostic Modeling.