Publications by Aritra
Discussion_!4
rm(list = ls()) I. library('stargazer') ## ## Please cite as: ## Hlavac, Marek (2022). stargazer: Well-Formatted Regression and Summary Statistics Tables. ## R package version 5.2.3. https://CRAN.R-project.org/package=stargazer 1. data = swiss summary(data) ## Fertility Agriculture Examination Education ## Min. :35.00 ...
5205 sym R (4513 sym/15 pcs) 1 img
Discussion_13
rm(list = ls()) #clear environment and remove all files from the workspace gc() #clear the unused memory ## used (Mb) gc trigger (Mb) limit (Mb) max used (Mb) ## Ncells 525901 28.1 1167874 62.4 NA 669400 35.8 ## Vcells 968927 7.4 8388608 64.0 16384 1851644 14.2 Choosing Dataset df = sleep head(df) ## extra grou...
505 sym Python (1588 sym/13 pcs) 1 img
Discusiion_13
rm(list = ls()) #clear environment and remove all files from the workspace gc() #clear the unused memory ## used (Mb) gc trigger (Mb) limit (Mb) max used (Mb) ## Ncells 525900 28.1 1167871 62.4 NA 669400 35.8 ## Vcells 968912 7.4 8388608 64.0 16384 1851644 14.2 Choosing Dataset df = sleep head(df) ## extra grou...
463 sym Python (1588 sym/13 pcs) 1 img
Discussion_12
#Clearing the environment rm(list = ls()) 1. Correlation Correlation is a statistical term that describes how much two variables fluctuate in tandem. A correlation coefficient of -1 shows a perfect negative correlation, which means that if one variable increases, so does the other. A correlation value of 0 shows that there is no linear relationshi...
1828 sym R (29688 sym/24 pcs)
Discussion_11
rm(list = ls()) #Importing libraries library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.3 ✔ readr 2.1.4 ## ✔ forcats 1.0.0 ✔ stringr 1.5.0 ## ✔ ggplot2 3.4.3 ✔ tibble 3.2.1 ## ✔ lubrid...
554 sym R (7062 sym/25 pcs) 2 img
Discussion_11
rm(list = ls()) #Importing libraries library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.3 ✔ readr 2.1.4 ## ✔ forcats 1.0.0 ✔ stringr 1.5.0 ## ✔ ggplot2 3.4.3 ✔ tibble 3.2.1 ## ✔ lubrid...
554 sym R (7062 sym/25 pcs) 2 img
Discussion_10
rm(list = ls()) Part 1 # Load necessary libraries library(ggplot2) library(dplyr) ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## intersect, setdiff, setequal, union # Load required libraries library(ggplot2) libra...
1967 sym R (2902 sym/9 pcs) 3 img
Discussion_9
1. Please Google and describe Law of Large Numbers in wer own words. This law is based on the idea that random events tend to average out over time. When we take a small sample from a large population, there might be some variability, and the sample average might not perfectly reflect the population average. However, as we increase the sample size,...
5988 sym 2 img
Discussion_9
set.seed(seed = 178) 1. Please Google and describe Law of Large Numbers in wer own words. This law is based on the idea that random events tend to average out over time. When we take a small sample from a large population, there might be some variability, and the sample average might not perfectly reflect the population average. However, as we incr...
5989 sym 2 img
Discussion_8
I. SAMPLING METHODOLOGIES 1. Probability and Non-probability sampling a. Probability Sampling: Probability sampling is a method of selecting a sample from a larger population in such a way that each element in the population has a known and non-zero chance of being included in the sample. It relies on random selection techniques, like simple rando...
5138 sym R (2103 sym/16 pcs) 2 img