Publications by Anurag
Week 11 Data Dive
library(ggrepel) ## Loading required package: ggplot2 library(boot) library(broom) library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.4 ✔ readr 2.1.4 ## ✔ forcats 1.0.0 ✔ stringr 1.5.1 ## ✔ lubrida...
5063 sym R (6224 sym/34 pcs) 8 img
Week 10 Data Dive
library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.4 ✔ readr 2.1.4 ## ✔ forcats 1.0.0 ✔ stringr 1.5.1 ## ✔ ggplot2 3.4.4 ✔ tibble 3.2.1 ## ✔ lubridate 1.9.3 ✔ tidyr 1.3.0 ## ...
264 sym R (1929 sym/9 pcs) 2 img
Statcast Project
Contents 1. Visualizing the age of the players vs xBA (expected Batting Average) 2. Visualizing the age of the players vs Barrels% library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.4 ✔ readr 2.1.4 ## ✔ forc...
811 sym R (2047 sym/5 pcs) 2 img
Week 9 Data Dive
Contents: 1. Multiple Linear Regression Model - using backward for selecting features. 2. Model Diagnosis and Evaluation - Diagnostic Plots - Influential data points library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1....
1048 sym R (8061 sym/26 pcs) 7 img
Week 8 Data Dive
Contents: 1. ANOVA - Finding the Runs Scored by teams in the three divisions (East, West, Central) 2. Linear Regression Model - Runs Scored and Batting Average of teams. library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1....
687 sym R (3208 sym/22 pcs) 2 img
Week - 7 Data Dive
Contents: 1. Two sample mean test - Comapring mean Runs per Game between American League and National League. 2. Similar test in Fisher’s Style - significance testing and visualizing the test. 3. Effect size calculation (Cohen’s d) 4. Calculating the minimum sample size required to perform hypothesis testing. 5. Fishers Exact test & Chi-sq...
3171 sym R (6521 sym/43 pcs) 3 img
Week 6 Data Dive
Table Of Contents: - Dividing the teams into categories based on 1. OBP performance. 2. SLG performance. 3. OPS (OBP+SLG) performance. - Response variable - Winning percentage (Win_Per) 1. OBP vs Win_Per 2. SLG vs Win_Per 3. OPS vs Win_Per -Response Variable - Wins (W) - Confidence Interval of W using Bootstrapping library(tidyverse) ## �...
4170 sym R (8364 sym/34 pcs) 5 img
Week - 5 Data Dive
library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.4 ✔ readr 2.1.4 ## ✔ forcats 1.0.0 ✔ stringr 1.5.1 ## ✔ ggplot2 3.4.4 ✔ tibble 3.2.1 ## ✔ lubridate 1.9.3 ✔ tidyr 1.3.0 ## ...
4182 sym R (54631 sym/13 pcs) 2 img
Week 4 Data Dive
Lets create 5 sample from the Lahman Database - (Each sample is 50% of the original data) library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.4 ✔ readr 2.1.4 ## ✔ forcats 1.0.0 ✔ stringr 1.5.1 ## ✔...
6319 sym R (19307 sym/33 pcs) 9 img 1 tbl
Data Dive Week 3
This RMarkdown contains: Finding out the anomalies in Average runs scored and winning percentage by defining our own threshold. (visualizing them using graphs) Probability concepts on Average runs scored and winning percentage group by franchID and finding out the under, avg and best performing teams from 2000-2022. (visualizing them using graphs)...
6854 sym R (13795 sym/45 pcs) 7 img 1 tbl