woRdle Play

Intro After watching 3Blue1Brown’s video on solving Wordle using information theory, I’ve decided to try my own method using a similar method using probability. His take on using word frequency and combining this with expected information gain quantified by bits for finding the solution was interesting. This is a great approach, especially when playing against a person, who may chose to play a word that’s not in the predefined list of the official Wordle webiste. [Read More]

UIUC Public GPA Dataset Exploration with Shiny

Last year, I thought it would be a good idea to dig through the GPA data set available from here. I started building a Shiny app that lets the user explore certain aspects of the data. Now, it’s almost been a year and I haven’t got the chance and the will to work on it until now. I made it really simple so that I can quickly move on to other topics instead of dragging this on for another year with an unfinished product. [Read More]

Grasping Power

I was reading a paper on calculation of sample sizes, and I inevitably came across the topic of statistical power. Essentially, when you’re designing on experiment, the sample size is an important factor to consider due to limiting resources. You want to have a sample size that is neither too small (which could result in high chance of failure to detect true differences) nor too big (potential waste of resources, albeit yielding better estimation). [Read More]

Sorting Comparison Pt. 2

Load all the datasets that I’ve saved from the previous benchmarks set.seed(12345) library(microbenchmark) library(tidyverse) library(knitr) library(kableExtra) load("2019-03-01-sorting-comparison/sort_comparisons") Blowing off the Dust I see that in my environment, two variables, special_case_sort_time and trend_sort_time are loaded. It’s been a long time since I’ve created these data, so I have an unclear memory as to what these objects are. Usually I use str, class to understand they are. I also make use of head to quickly glance at the data usually if it is a data. [Read More]

Sorting Comparison

As I’m self studying algorithms and data structures with python from here, I figured I could try to do some experiments with different sorting algorithms using my own implementations in R. Types of sorting algorithms I will use: Bubble Sort Insertion Sort Selection Sort Shell Sort Merge Sort Quick Sort I will be dealing with a vector of type double. It can be a collection of any real positive numbers. [Read More]
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