gaurav soodoku

## stratified_vs_srs.R

-------------

set.seed(123)

# Step 1: Simulate Population
num_strata <- 10  # Number of strata
population_size <- 100000  # Total population size

# Generate strata sizes and proportions

## demand_supply.R
# Set random seed for reproducibility
set.seed(123)

# Time t parameters
n_novels_x_t <- 500    # 50% of 1000 novels are type x at time t
n_novels_y_t <- 500
k <- 30               # 30% more likely to read type x
total_readings <- 800 # Fixed total reading capacity

# Time t simulation

## attenuation.R
# Set seed for reproducibility
set.seed(123)

# Number of observations
n <- 1000

# Simulate a perfectly measured outcome (Y_perfect)
# Treatment effect
treatment_effect <- 5
base_noise <- rnorm(n, mean = 0, sd = 1)  # Base noise for the perfect outcome

## shrug_2011_vd.R
library(readr)
shrug <- read_csv("/Users/soodoku/Downloads/shrug-vd11-csv/pc11_vd_clean_shrid.csv")

# Take out missing from village pop (just 1) and sort
t_pop <- shrug$pc11_vd_t_p[!is.na(shrug$pc11_vd_t_p)]
sorted_values <- sort(t_pop, decreasing = TRUE)

# We have like 570k villages. 50k villages have ...
sum(sorted_values[1:50000])/sum(sorted_values)
# [1] 0.3720554

## jokes.md

      
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                soodoku
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              January 25, 2024 23:53
            
              
                Jokes
              
          
What virus did Gautam Budh Have? Karuna virus.
Deva o deva, deva o deva, tumse badkar kaun ....? Tumhara baap
Which kinds of people don't have a magnetic personality? People with no sense of irony.
What does a bald Muslim man want most? Iqbal


## guaranteed_rewards.md

      
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              Last active
              November 16, 2023 06:04
            
              
                Guaranteed Rewards
              
          
    Self Marketing in Prayers

Laxmi Aarti

महालक्ष्मी जी की आरती,

जो कोई नर गाता ।

उँर आंनद समाता,

पाप उतर जाता ॥

  
## bihar_jati_2022.csv

          
            page
            क्र ० सं ०
            जाति
            आंकड़ा
            प्रतिशत ( % )

            
              0
              1
              अघोरी
              9039
              0.0069 %

            
              0
              2
              अदरखी
              30857
              0.0236 %

            
              0
              3
              अबदल
              11433
              0.0087 %

            
              0
              4
              अमात
              285221
              0.2182 %

            
              0
              5
              अवध बनिया
              41643
              0.0319 %

            
              0
              6
              असुर , अगरिया
              7706
              0.0059 %

            
              0
              7
              इदरीसी या दर्जी ( मुस्लिम )
              329661
              0.2522 %

            
              0
              8
              ईटफरोश / ईटाफरोश / गदहेड़ी / ईटपज इब्राहिमी ( मुस्लिम )
              9462
              0.0072 %

            
              0
              9
              इसाई धर्मावलंबी ( हरिजन )
              9708
              0.0074 %

## TrainingV3.ipynb

      
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              Created
              October 8, 2023 19:14
            
              
                Facial Sentiment Classifier
              
          
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## senator_ed.csv
State,Name,Party,Rel.,Prior Exp.,Education,Year in,Born,Top College,R Top Coll.,D Top Coll.,Ad. Degree,R ,D
Alabama ,Richard Shelby ,Republican ,Presbyterian ,"U.S. House, Alabama Senate ","Alabama (BA, JD) ",1987,1934,,0,0,1,1,0
Alabama ,"Sessions, JeffJeff Sessions ",Republican ,Methodist ,Alabama Attorney General ,"Huntingdon College, University of Alabama ",1997,1946,,0,0,1,1,0
Alaska ,"Murkowski, LisaLisa Murkowski ",Republican ,Roman Catholic ,Alaska House of Representatives ,"Georgetown, Willamette ",2002,1957,,0,0,1,1,0
Alaska ,"Begich, MarkMark Begich ",Democratic ,Roman Catholic ,Mayor of Anchorage ,University of Alaska Anchorage (attended) ,2009,1962,,0,0,,0,0
Arizona ,"McCain, JohnJohn McCain ",Republican ,Baptist[1] ,"U.S. House, military ",U.S. Naval Academy[2] ,1987,1936,,0,0,1,1,0
Arizona ,"Kyl, JonJon Kyl ",Republican ,Presbyterian ,U.S. House ,"Arizona (BA, JD) ",1995,1942,,0,0,1,1,0
Arkansas ,"Lincoln, BlancheBlanche Lincoln ",Democratic ,Episcopalian ,U.S. House ,"Randolph-Macon Women\'s C

## towns.csv
Alabama,Abanda,33.10,-85.53,639
Alabama,Abbeville,31.57,-85.25,426
Alabama,Abbot Springs,33.36,-86.48,600
Alabama,Abel,33.55,-85.71,912
Alabama,Abercrombie,32.85,-87.16,291
Alabama,Aberfoil,32.07,-85.69,600
Alabama,Abernant,33.29,-87.20,459
Alabama,Abernathy,33.65,-85.41,1000
Alabama,Abernathy (historical),33.80,-85.57,1282
Alabama,Abihka (historical),33.30,-86.16,600

	-------------

	set.seed(123)

	# Step 1: Simulate Population
	num_strata <- 10 # Number of strata
	population_size <- 100000 # Total population size

	# Generate strata sizes and proportions
	# Set random seed for reproducibility
	set.seed(123)

	# Time t parameters
	n_novels_x_t <- 500 # 50% of 1000 novels are type x at time t
	n_novels_y_t <- 500
	k <- 30 # 30% more likely to read type x
	total_readings <- 800 # Fixed total reading capacity

	# Time t simulation
	# Set seed for reproducibility
	set.seed(123)

	# Number of observations
	n <- 1000

	# Simulate a perfectly measured outcome (Y_perfect)
	# Treatment effect
	treatment_effect <- 5
	base_noise <- rnorm(n, mean = 0, sd = 1) # Base noise for the perfect outcome
	library(readr)
	shrug <- read_csv("/Users/soodoku/Downloads/shrug-vd11-csv/pc11_vd_clean_shrid.csv")

	# Take out missing from village pop (just 1) and sort
	t_pop <- shrug$pc11_vd_t_p[!is.na(shrug$pc11_vd_t_p)]
	sorted_values <- sort(t_pop, decreasing = TRUE)

	# We have like 570k villages. 50k villages have ...
	sum(sorted_values[1:50000])/sum(sorted_values)
	# [1] 0.3720554
page	क्र ० सं ०	जाति	आंकड़ा	प्रतिशत ( % )
0	1	अघोरी	9039	0.0069 %
0	2	अदरखी	30857	0.0236 %
0	3	अबदल	11433	0.0087 %
0	4	अमात	285221	0.2182 %
0	5	अवध बनिया	41643	0.0319 %
0	6	असुर , अगरिया	7706	0.0059 %
0	7	इदरीसी या दर्जी ( मुस्लिम )	329661	0.2522 %
0	8	ईटफरोश / ईटाफरोश / गदहेड़ी / ईटपज इब्राहिमी ( मुस्लिम )	9462	0.0072 %
0	9	इसाई धर्मावलंबी ( हरिजन )	9708	0.0074 %
	State,Name,Party,Rel.,Prior Exp.,Education,Year in,Born,Top College,R Top Coll.,D Top Coll.,Ad. Degree,R ,D
	Alabama ,Richard Shelby ,Republican ,Presbyterian ,"U.S. House, Alabama Senate ","Alabama (BA, JD) ",1987,1934,,0,0,1,1,0
	Alabama ,"Sessions, JeffJeff Sessions ",Republican ,Methodist ,Alabama Attorney General ,"Huntingdon College, University of Alabama ",1997,1946,,0,0,1,1,0
	Alaska ,"Murkowski, LisaLisa Murkowski ",Republican ,Roman Catholic ,Alaska House of Representatives ,"Georgetown, Willamette ",2002,1957,,0,0,1,1,0
	Alaska ,"Begich, MarkMark Begich ",Democratic ,Roman Catholic ,Mayor of Anchorage ,University of Alaska Anchorage (attended) ,2009,1962,,0,0,,0,0
	Arizona ,"McCain, JohnJohn McCain ",Republican ,Baptist[1] ,"U.S. House, military ",U.S. Naval Academy[2] ,1987,1936,,0,0,1,1,0
	Arizona ,"Kyl, JonJon Kyl ",Republican ,Presbyterian ,U.S. House ,"Arizona (BA, JD) ",1995,1942,,0,0,1,1,0
	Arkansas ,"Lincoln, BlancheBlanche Lincoln ",Democratic ,Episcopalian ,U.S. House ,"Randolph-Macon Women\'s C
	Alabama,Abanda,33.10,-85.53,639
	Alabama,Abbeville,31.57,-85.25,426
	Alabama,Abbot Springs,33.36,-86.48,600
	Alabama,Abel,33.55,-85.71,912
	Alabama,Abercrombie,32.85,-87.16,291
	Alabama,Aberfoil,32.07,-85.69,600
	Alabama,Abernant,33.29,-87.20,459
	Alabama,Abernathy,33.65,-85.41,1000
	Alabama,Abernathy (historical),33.80,-85.57,1282
	Alabama,Abihka (historical),33.30,-86.16,600