EA_Rural India
knitr::opts_chunk$set(echo = TRUE)
library(dplyr)## Warning: package 'dplyr' was built under R version 4.0.4##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(readr)
library(haven)
library(ggthemes)## Warning: package 'ggthemes' was built under R version 4.0.5library(rstatix)## Warning: package 'rstatix' was built under R version 4.0.5##
## Attaching package: 'rstatix'## The following object is masked from 'package:stats':
##
## filterlibrary(esquisse)
library(haven)
library(vtable)## Warning: package 'vtable' was built under R version 4.0.5## Loading required package: kableExtra## Warning: package 'kableExtra' was built under R version 4.0.5##
## Attaching package: 'kableExtra'## The following object is masked from 'package:dplyr':
##
## group_rowslibrary(ggplot2)
library(purrr)
data <- read.csv("A:/Angira/USFCA/Altruism/Rural data analysis/(IN) - Giver Motives Across Cultures - Rural Group_June 22, 2022_10.27.csv")
head(data)## StartDate EndDate Status IPAddress Progress
## 1 19-06-2022 22:48 19-06-2022 23:14 IP Address 180.94.32.1 100
## 2 19-06-2022 20:32 19-06-2022 23:14 IP Address 180.94.32.1 100
## 3 19-06-2022 22:50 19-06-2022 23:17 IP Address 180.94.32.1 100
## 4 19-06-2022 22:49 19-06-2022 23:23 IP Address 180.94.32.1 100
## 5 19-06-2022 22:49 19-06-2022 23:25 IP Address 180.94.32.1 100
## 6 19-06-2022 22:46 19-06-2022 23:28 IP Address 47.15.39.239 100
## Duration..in.seconds. Finished RecordedDate ResponseId
## 1 1578 TRUE 19-06-2022 23:14 R_1PRwjXJmafKc7U8
## 2 9700 TRUE 19-06-2022 23:14 R_1jBrtRBRpOUJbhr
## 3 1640 TRUE 19-06-2022 23:18 R_VPfJPunqmq4J25H
## 4 2049 TRUE 19-06-2022 23:23 R_28ORetXK7x7irvb
## 5 2126 TRUE 19-06-2022 23:25 R_1nTmq5lJ4w1bHuo
## 6 2503 TRUE 19-06-2022 23:28 R_DA98a8T0Lmj2oFj
## RecipientLastName RecipientFirstName RecipientEmail ExternalReference
## 1 NA NA NA NA
## 2 NA NA NA NA
## 3 NA NA NA NA
## 4 NA NA NA NA
## 5 NA NA NA NA
## 6 NA NA NA NA
## LocationLatitude LocationLongitude DistributionChannel UserLanguage
## 1 29.4742 77.7027 anonymous EN
## 2 29.4742 77.7027 anonymous EN
## 3 29.4742 77.7027 anonymous EN
## 4 29.4742 77.7027 anonymous EN
## 5 29.4742 77.7027 anonymous EN
## 6 22.5180 88.3832 anonymous EN
## Q_RecaptchaScore Q_RelevantIDDuplicate Q_RelevantIDDuplicateScore
## 1 1 TRUE 100
## 2 1 TRUE 100
## 3 1 TRUE 100
## 4 1 TRUE 100
## 5 1 TRUE 100
## 6 NA NA NA
## Q_RelevantIDFraudScore Q_RelevantIDLastStartDate Country_Origin
## 1 0 18-06-2022 06:49 India (à¤à¤¾à¤°à¤¤)
## 2 0 15-06-2022 18:52 India (à¤à¤¾à¤°à¤¤)
## 3 0 17-06-2022 13:21 India (à¤à¤¾à¤°à¤¤)
## 4 0 19-06-2022 06:28 India (à¤à¤¾à¤°à¤¤)
## 5 0 19-06-2022 06:27 India (à¤à¤¾à¤°à¤¤)
## 6 NA India (à¤à¤¾à¤°à¤¤)
## Country_living
## 1 India (à¤à¤¾à¤°à¤¤)
## 2 India (à¤à¤¾à¤°à¤¤)
## 3 India (à¤à¤¾à¤°à¤¤)
## 4 India (à¤à¤¾à¤°à¤¤)
## 5 India (à¤à¤¾à¤°à¤¤)
## 6 India (à¤à¤¾à¤°à¤¤)
## Consent
## 1 Yes, I consent मà¥\201à¤\235े à¤à¤¾à¤— लेना हà¥\210
## 2 Yes, I consent मà¥\201à¤\235े à¤à¤¾à¤— लेना हà¥\210
## 3 Yes, I consent मà¥\201à¤\235े à¤à¤¾à¤— लेना हà¥\210
## 4 Yes, I consent मà¥\201à¤\235े à¤à¤¾à¤— लेना हà¥\210
## 5 Yes, I consent मà¥\201à¤\235े à¤à¤¾à¤— लेना हà¥\210
## 6 Yes, I consent मà¥\201à¤\235े à¤à¤¾à¤— लेना हà¥\210
## AttentionCheck
## 1 I canâ\200\231t promise either way हम वादा नहà¥\200ं कर सकà¥\215ते
## 2 Yes, I will हाà¤\201
## 3 Yes, I will हाà¤\201
## 4 Yes, I will हाà¤\201
## 5 Yes, I will हाà¤\201
## 6 Yes, I will हाà¤\201
## Residential.Area Residential.Live Age
## 1 Rural गà¥\215राम/जिला Yes हाà¤\201 50
## 2 Rural गà¥\215राम/जिला Yes हाà¤\201 75
## 3 Rural गà¥\215राम/जिला No नहà¥\200ं 70
## 4 Rural गà¥\215राम/जिला No नहà¥\200ं 59
## 5 Rural गà¥\215राम/जिला Yes हाà¤\201 60
## 6 Rural गà¥\215राम/जिला Yes हाà¤\201 35
## ObjectiveSES_2 ObjectiveSES_1
## 1 Less than high school degree (12th से कम ) Less than INR 10,000
## 2 Less than high school degree (12th से कम ) Less than INR 10,000
## 3 Less than high school degree (12th से कम ) Less than INR 10,000
## 4 Less than high school degree (12th से कम ) Less than INR 10,000
## 5 Less than high school degree (12th से कम ) Less than INR 10,000
## 6 Less than high school degree (12th से कम ) INR 10,000 -INR 30,000
## Gender Gender_3_TEXT Race Race_7_TEXT
## 1 Female सà¥\215तà¥\215रà¥\200 NA Indian/Asian
## 2 Male पà¥\201रà¥\201ष NA Indian/Asian
## 3 Female सà¥\215तà¥\215रà¥\200 NA Indian/Asian
## 4 Female सà¥\215तà¥\215रà¥\200 NA Indian/Asian
## 5 Female सà¥\215तà¥\215रà¥\200 NA Indian/Asian
## 6 Female सà¥\215तà¥\215रà¥\200 NA Indian/Asian
## children.
## 1 Yes (if yes, please list their age and gender(s)) हाà¤\201 (कृपया बचà¥\215चों कà¥\200 उमà¥\215र और लिंग नà¥\200चे लिखे):
## 2 Yes (if yes, please list their age and gender(s)) हाà¤\201 (कृपया बचà¥\215चों कà¥\200 उमà¥\215र और लिंग नà¥\200चे लिखे):
## 3 Yes (if yes, please list their age and gender(s)) हाà¤\201 (कृपया बचà¥\215चों कà¥\200 उमà¥\215र और लिंग नà¥\200चे लिखे):
## 4 Yes (if yes, please list their age and gender(s)) हाà¤\201 (कृपया बचà¥\215चों कà¥\200 उमà¥\215र और लिंग नà¥\200चे लिखे):
## 5 Yes (if yes, please list their age and gender(s)) हाà¤\201 (कृपया बचà¥\215चों कà¥\200 उमà¥\215र और लिंग नà¥\200चे लिखे):
## 6 Yes (if yes, please list their age and gender(s)) हाà¤\201 (कृपया बचà¥\215चों कà¥\200 उमà¥\215र और लिंग नà¥\200चे लिखे):
## children._1_TEXT family_size
## 1 3 small छोटा परिवार
## 2 1 small छोटा परिवार
## 3 3boys 40age 1girl 30 large बड़ा परिवार
## 4 2 boy 1 girl large बड़ा परिवार
## 5 2 ladki 1 ladka large बड़ा परिवार
## 6 (2-B25,19)2- G(26-20) large बड़ा परिवार
## Political_orient
## 1 Yes, a little थोड़ा सा
## 2 Yes, a little थोड़ा सा
## 3 No. Absolutely not बिलà¥\215कà¥\201ल नहà¥\200ं
## 4 Yes, a little थोड़ा सा
## 5 Yes, a little थोड़ा सा
## 6 No, not really नहà¥\200ं
## PoliticalParty
## 1 against protesting पà¥\215रदरà¥\215शन के विरोध में
## 2 against protesting पà¥\215रदरà¥\215शन के विरोध में
## 3 in support of protesting पà¥\215रदरà¥\215शन के समरà¥\215थन में
## 4 in support of protesting पà¥\215रदरà¥\215शन के समरà¥\215थन में
## 5 against protesting पà¥\215रदरà¥\215शन के विरोध में
## 6 against protesting पà¥\215रदरà¥\215शन के विरोध में
## Political_Strength
## 1 Strongly बोहोत जà¥\215यादा
## 2 Not very strongly थोड़ा
## 3 Not very strongly थोड़ा
## 4 Not very strongly थोड़ा
## 5 Not very strongly थोड़ा
## 6 Strongly बोहोत जà¥\215यादा
## Tax_importance
## 1 Not at all important बिलà¥\215कà¥\201ल नहà¥\200ं
## 2 Moderately important थोड़ा जरूरà¥\200 हà¥\210
## 3 Slightly important बहà¥\201त थोड़ा ज़रूरà¥\200
## 4 Very important ज़रूरà¥\200 हà¥\210
## 5 Very important ज़रूरà¥\200 हà¥\210
## 6 Not at all important बिलà¥\215कà¥\201ल नहà¥\200ं
## Religion Caste
## 1 Agnostic or atheist (नासà¥\215तिक) General-Other religions
## 2 Hindu (हिनà¥\215दू) Scheduled Caste (SC)
## 3 Hindu (हिनà¥\215दू) Scheduled Caste (SC)
## 4 Hindu (हिनà¥\215दू) Scheduled Caste (SC)
## 5 Hindu (हिनà¥\215दू) Scheduled Caste (SC)
## 6 Agnostic or atheist (नासà¥\215तिक) Scheduled Tribe (ST)
## Enjoy_activities_1 Enjoy_activities_2 Enjoy_activities_3 Enjoy_activities_4
## 1 5 1 4 2
## 2 6 2 3 1
## 3 2 7 6 5
## 4 6 3 2 1
## 5 4 3 2 1
## 6 7 4 2 1
## Enjoy_activities_5 Enjoy_activities_6 Enjoy_activities_7 PersonalExperience_1
## 1 6 7 3 3
## 2 4 7 5 8
## 3 1 4 3 8
## 4 4 7 5 9
## 5 6 5 7 5
## 6 3 6 5 5
## PersonalExperience_2 PersonalExperience_3 PersonalExperience_4
## 1 2 8 7
## 2 3 4 7
## 3 7 4 5
## 4 1 4 7
## 5 8 2 9
## 6 4 7 2
## PersonalExperience_5 PersonalExperience_6 PersonalExperience_7
## 1 4 5 1
## 2 6 5 1
## 3 9 2 1
## 4 6 5 3
## 5 7 3 1
## 6 6 9 1
## PersonalExperience_8 PersonalExperience_9 PassionProblem_1 PassionProblem_2
## 1 9 6 5 4
## 2 2 9 6 5
## 3 6 3 7 6
## 4 2 8 3 5
## 5 4 6 3 6
## 6 8 3 4 2
## PassionProblem_3 PassionProblem_4 PassionProblem_5 PassionProblem_12
## 1 3 1 6 2
## 2 1 3 4 7
## 3 2 1 3 5
## 4 6 1 2 7
## 5 2 1 5 7
## 6 5 1 3 6
## PassionProblem_13 Q86_First.Click Q86_Last.Click Q86_Page.Submit
## 1 7 0.948 2.278 41.649
## 2 2 2.223 15.928 16.509
## 3 4 2.197 24.113 24.981
## 4 4 0.722 56.349 56.993
## 5 4 1.036 26.726 27.305
## 6 7 3.807 29.873 30.740
## Q86_Click.Count GI_check1 GI_check2
## 1 2 Yes, they represent real charities हाà¤\201 Charity A
## 2 7 Yes, they represent real charities हाà¤\201 Charity A
## 3 9 Yes, they represent real charities हाà¤\201 Charity A
## 4 9 Yes, they represent real charities हाà¤\201 Charity A
## 5 14 Yes, they represent real charities हाà¤\201 Charity A
## 6 4 Yes, they represent real charities हाà¤\201 Charity A
## GI_check3 CG_timing_First.Click CG_timing_Last.Click CG_timing_Page.Submit
## 1 Charity B 1.041 50.077 50.975
## 2 Charity B 15.529 24.564 25.100
## 3 Charity B 0.035 12.985 26.925
## 4 Charity B 16.880 45.217 46.087
## 5 Charity B 2.017 39.413 40.063
## 6 Charity B 2.263 31.126 31.821
## CG_timing_Click.Count Char_Community_1 Char_Community_2 Char_Caste._1
## 1 7 10 90 10
## 2 3 50 50 80
## 3 14 10 90 10
## 4 8 70 30 70
## 5 10 70 30 50
## 6 12 50 50 50
## Char_Caste._2 Char_Country_1 Char_Country_2 Char_Ideology_1 Char_Ideology_2
## 1 90 10 90 10 90
## 2 20 60 40 50 50
## 3 90 10 90 40 60
## 4 30 50 50 50 50
## 5 50 40 60 30 70
## 6 50 40 60 20 80
## Char_Religion_1 Char_Religion_2 Char_Generation_1 Char_Generation_2
## 1 10 90 10 90
## 2 50 50 60 40
## 3 50 50 50 50
## 4 80 20 50 50
## 5 50 50 50 50
## 6 40 60 50 50
## Char_Species_1 Char_Species_2 Char_CausePriority_1 Char_CausePriority_2
## 1 10 90 10 90
## 2 60 40 50 50
## 3 20 80 40 60
## 4 70 30 90 10
## 5 50 50 30 70
## 6 40 60 40 60
## Char_CausePassion_1 Char_CausePassion_2 Norms_timing_First.Click
## 1 10 90 0.706
## 2 70 30 2.019
## 3 50 50 1.322
## 4 30 70 1.035
## 5 30 70 0.812
## 6 80 20 1.039
## Norms_timing_Last.Click Norms_timing_Page.Submit Norms_timing_Click.Count
## 1 16.518 17.501 6
## 2 40.579 41.437 3
## 3 14.340 18.022 7
## 4 13.175 16.201 10
## 5 28.476 39.976 10
## 6 30.215 31.251 8
## Norm_Community_1 Norm_Community_2 Norm_Caste_1 Norm_Caste_2 Norm_Country_1
## 1 10 90 10 90 10
## 2 50 50 80 20 70
## 3 50 50 10 90 10
## 4 90 10 80 20 50
## 5 80 20 50 50 50
## 6 50 50 50 50 50
## Norm_Country_2 Norm_Ideology_1 Norm_Ideology_2 Norm_Religion_1
## 1 90 10 90 10
## 2 30 50 50 80
## 3 90 20 80 10
## 4 50 90 10 80
## 5 50 30 70 50
## 6 50 10 90 60
## Norm_Religion_2 Norm_Generation_1 Norm_Generation_2 Norm_Species_1
## 1 90 10 90 10
## 2 20 60 40 70
## 3 90 50 50 40
## 4 20 80 20 90
## 5 50 50 50 30
## 6 40 90 10 50
## Norm_Species_2 Norm_CausPriority_1 Norm_CausPriority_2 Norm_CausePassion_1
## 1 90 10 90 10
## 2 30 60 40 70
## 3 60 40 60 50
## 4 10 80 20 70
## 5 70 30 70 70
## 6 50 50 50 50
## Norm_CausePassion_2 Char_Generosity N_Generosity2 Anika William
## 1 90 700 700 20 80
## 2 30 4000 3000 4000 4000
## 3 50 2000 500 1000 1000
## 4 30 2000 3000 1000 1000
## 5 30 3000 3000 1500 1500
## 6 50 4000 4500 3000 1000
## ObjectiveSES_3
## 1 Less than high school degree (12 से कम)
## 2 Less than high school degree (12 से कम)
## 3 Less than high school degree (12 से कम)
## 4 Less than high school degree (12 से कम)
## 5 Less than high school degree (12 से कम)
## 6 Less than high school degree (12 से कम)
## ObjectiveSES_4
## 1 Less than high school degree (12 से kam)
## 2 Less than high school degree (12 से kam)
## 3 Less than high school degree (12 से kam)
## 4 Less than high school degree (12 से kam)
## 5 Less than high school degree (12 से kam)
## 6 Less than high school degree (12 से kam)
## SubjectiveSES_1
## 1 Upper-middle class ऊपरà¥\200 मधà¥\215य वरà¥\215ग
## 2 Lower class निमà¥\215न वरà¥\215ग
## 3 Lower-middle class निमà¥\215न मधà¥\215यम वरà¥\215ग
## 4 Lower class निमà¥\215न वरà¥\215ग
## 5 Lower class निमà¥\215न वरà¥\215ग
## 6 Lower class निमà¥\215न वरà¥\215ग
## SubjectiveSES_2_1
## 1
## 2 Rung 2
## 3 Rung 8
## 4 Rung 2
## 5 Rung 1
## 6 Rung 1
## SubjectiveSES_3_1
## 1 Somewhat Agree थोड़ा सहमत
## 2 Agree सहमत
## 3 Strongly Agree बोहोत सहमत
## 4 Somewhat Agree थोड़ा सहमत
## 5 Strongly Disagree बिलà¥\215कà¥\201ल असहमत
## 6 Neither Agree Nor Disagree ना सहमत ना असहमत
## SubjectiveSES_3_2
## 1 Agree सहमत
## 2 Agree सहमत
## 3 Somewhat Agree थोड़ा सहमत
## 4 Somewhat Agree थोड़ा सहमत
## 5 Strongly Disagree बिलà¥\215कà¥\201ल असहमत
## 6 Strongly Disagree बिलà¥\215कà¥\201ल असहमत
## SubjectiveSES_3_3
## 1 Somewhat Disagree थोड़ा असहमत
## 2 Agree सहमत
## 3 Somewhat Agree थोड़ा सहमत
## 4 Agree सहमत
## 5 Strongly Disagree बिलà¥\215कà¥\201ल असहमत
## 6 Strongly Disagree बिलà¥\215कà¥\201ल असहमत
## SubjectiveSES_3_4 location_name
## 1 Strongly Agree बोहोत सहमत Nagar Chaugwan
## 2 Agree सहमत Nagar chaugwan
## 3 Disagree असहमत Kheria
## 4 Agree सहमत Nagar chaugwan
## 5 Strongly Disagree बिलà¥\215कà¥\201ल असहमत Itoja
## 6 Strongly Disagree बिलà¥\215कà¥\201ल असहमत Chaugava
## culture
## 1 Family
## 2 Friends , relatives and near me
## 3 Relative
## 4 Na
## 5 Not
## 6
## Culture
## 1 My close friends and family मेरा परिवार और दोसà¥\215त
## 2 My close friends and family मेरा परिवार और दोसà¥\215त
## 3 People who live near me जो मेरे आस पास रहते हà¥\210
## 4 People who live near me जो मेरे आस पास रहते हà¥\210
## 5 People who share my same caste मेरà¥\200 जातà¥\200 के लोग
## 6 People who live near me जो मेरे आस पास रहते हà¥\210
## Culture_8_TEXT location surveyor_idÂ. Condition
## 1 226203 AP-1476 Giving 1st
## 2 226203 VG-7833 Norms 1st
## 3 226203 AS_7382 Giving 1st
## 4 226203 Ts - 3628 Norms 1st
## 5 226203 SV5372 Giving 1st
## 6 226203 VP-7257 Norms 1st
## country_mismatch
## 1 Mexico (मेकà¥\215सिको)
## 2 South Africa (अफà¥\215रà¥\200का)
## 3 the United States (अमेरिका)
## 4 Mexico (मेकà¥\215सिको)
## 5 South Africa (अफà¥\215रà¥\200का)
## 6 Mexico (मेकà¥\215सिको)
## Anika_physicaldist Acountry_match
## 1 Mexico (मेकà¥\215सिको) 0
## 2 South Africa (अफà¥\215रà¥\200का) 0
## 3 India (à¤à¤¾à¤°à¤¤) 1
## 4 Mexico (मेकà¥\215सिको) 0
## 5 India (à¤à¤¾à¤°à¤¤) 1
## 6 India (à¤à¤¾à¤°à¤¤) 1
## William_physicaldist Wcountry_match
## 1 India (à¤à¤¾à¤°à¤¤) 1
## 2 India (à¤à¤¾à¤°à¤¤) 1
## 3 the United States (अमेरिका) 0
## 4 India (à¤à¤¾à¤°à¤¤) 1
## 5 South Africa (अफà¥\215रà¥\200का) 0
## 6 Mexico (मेकà¥\215सिको) 0
## Anika_religion Areligion_match
## 1 religious (धारà¥\215मिक) 0
## 2 non-religious (नासà¥\215तिक) 0
## 3 Hindu (हिनà¥\215दू) 1
## 4 non-religious (नासà¥\215तिक) 0
## 5 Hindu (हिनà¥\215दू) 1
## 6 non-religious (नासà¥\215तिक) 1
## William_religion Wreligion_match
## 1 non-religious (नासà¥\215तिक) 1
## 2 Hindu (हिनà¥\215दू) 1
## 3 non-religious (नासà¥\215तिक) 0
## 4 Hindu (हिनà¥\215दू) 1
## 5 non-religious (नासà¥\215तिक) 0
## 6 religious (धारà¥\215मिक) 0
## Anika_family Afamily_match
## 1 large बड़ा परिवार 0
## 2 small छोटा परिवार 1
## 3 small छोटा परिवार 0
## 4 small छोटा परिवार 0
## 5 large बड़ा परिवार 1
## 6 large बड़ा परिवार 1
## William_family Wfamily_match
## 1 small छोटा परिवार 1
## 2 large बड़ा परिवार 0
## 3 large बड़ा परिवार 1
## 4 large बड़ा परिवार 1
## 5 small छोटा परिवार 0
## 6 small छोटा परिवार 0
## Anika_hobby
## 1 playing with animals and pets (जानवरों के साथ खेलना)
## 2 arts and crafts (कला)
## 3 learning new things (नà¤\210 चà¥\200जों के बारे में जानना)
## 4 cooking (खाना बनाना)
## 5 singing and listening to music (गाना या गानों को सà¥\201नना)
## 6 cooking (खाना बनाना)
## Ahobby_match
## 1 1
## 2 0
## 3 1
## 4 1
## 5 0
## 6 1
## William_hobby
## 1 arts and crafts (कला)
## 2 cooking (खाना बनाना)
## 3 playing with animals and pets (जानवरों के साथ खेलना)
## 4 arts and crafts (कला)
## 5 cooking (खाना बनाना)
## 6 playing sports (खेल कूद)
## Whobby_match
## 1 0
## 2 1
## 3 0
## 4 0
## 5 1
## 6 0
## Anika_affliction
## 1 addiction (alcohol or drug) नशा (शराब या धूमà¥\215रपान)
## 2 HIV/AIDs
## 3 addiction (alcohol or drug) नशा (शराब या धूमà¥\215रपान)
## 4 malnutrition and hunger (à¤à¥‚कमारà¥\200/कà¥\201पोषण)
## 5 addiction (alcohol or drug) नशा (शराब या धूमà¥\215रपान)
## 6 addiction (alcohol or drug) नशा (शराब या धूमà¥\215रपान)
## Aaffliction_match
## 1 1
## 2 0
## 3 1
## 4 0
## 5 1
## 6 1
## William_affliction
## 1 addiction (alcohol or drug) नशा (शराब या धूमà¥\215रपान)
## 2 addiction (alcohol or drug) नशा (शराब या धूमà¥\215रपान)
## 3 addiction (alcohol or drug) नशा (शराब या धूमà¥\215रपान)
## 4 homelessness (बेà¤\230र होना)
## 5 addiction (alcohol or drug) नशा (शराब या धूमà¥\215रपान)
## 6 addiction (alcohol or drug) नशा (शराब या धूमà¥\215रपान)
## Waffliction_match Anika_y. William_y. Anika_xfold William_xfold
## 1 0 20 10 2 2
## 2 1 10 40 5 5
## 3 0 50 50 3 2
## 4 1 30 30 4 3
## 5 0 50 20 2 4
## 6 0 10 50 2 5
## Anika_caste Acaste William_caste Wcaste
## 1 Shopkeeper दà¥\201कानदारों UC NA NA
## 2 Labourer मजदूरों LC NA NA
## 3 Shopkeeper दà¥\201कानदारों UC NA NA
## 4 Labourer मजदूरों LC NA NA
## 5 Shopkeeper दà¥\201कानदारों UC NA NA
## 6 Labourer मजदूरों LC NA NACleaning
data$Gender_new <- "Other"
data$Gender_new[data$Gender== "Female सà¥\u008dतà¥\u008dरी" ] <- "Female"
data$Gender_new[data$Gender == "Male पà¥\u0081रà¥\u0081ष"] <- "Male"
table(data$Gender_new)##
## Female Male Other
## 189 120 2data$children <- "No"
data$children[data$children.== "Yes (if yes, please list their age and gender(s)) हाà¤\u0081 (कृपया बचà¥\u008dचों की उमà¥\u008dर और लिंग नीचे लिखे):"] <- "Yes"
table(data$children)##
## No Yes
## 42 269data$Residential_Area[data$Residential.Area== "Urban शहर"] <- "Urban"
data$Residential_Area[data$Residential.Area== "Rural गà¥\u008dराम/जिला"] <- "Rural"
table(data$Residential_Area)##
## Rural Urban
## 307 2Summarising
Demographic
gender <- data %>%
group_by(Gender_new) %>%
summarise(counts = n())
gender## # A tibble: 3 x 2
## Gender_new counts
## <chr> <int>
## 1 Female 189
## 2 Male 120
## 3 Other 2gender %>% ggplot()+geom_bar(aes(x= Gender_new,y=counts), stat="identity", fill="steelblue4", alpha=0.9)+labs(title = "Gender distribution",
y = "Number of people",
x = "") 
children <- data %>%
group_by(children) %>%
summarise(counts = n())
children %>% ggplot()+geom_bar(aes(x= children,y=counts), stat="identity", fill="steelblue4", alpha=0.9)+labs(title = "Do you have any Children?", y = "Number of people",
x = "") 
Personal Decisions
Personal_C <- data %>%
select(Char_Community_2, Char_Caste._2, Char_Country_2 ,Char_Ideology_2,
Char_Religion_2, Char_Generation_2, Char_Species_2, Char_CausePriority_2,
Char_CausePassion_2)
summary(Personal_C)## Char_Community_2 Char_Caste._2 Char_Country_2 Char_Ideology_2
## Min. : 0.00 Min. : 0.00 Min. : 0.0 Min. : 0.00
## 1st Qu.: 50.00 1st Qu.: 30.00 1st Qu.: 10.0 1st Qu.: 50.00
## Median : 50.00 Median : 50.00 Median : 50.0 Median : 50.00
## Mean : 52.51 Mean : 46.08 Mean : 41.3 Mean : 53.98
## 3rd Qu.: 70.00 3rd Qu.: 60.00 3rd Qu.: 50.0 3rd Qu.: 70.00
## Max. :100.00 Max. :100.00 Max. :100.0 Max. :100.00
## Char_Religion_2 Char_Generation_2 Char_Species_2 Char_CausePriority_2
## Min. : 0.00 Min. : 0.00 Min. : 0.00 Min. : 0.00
## 1st Qu.: 20.00 1st Qu.: 30.00 1st Qu.: 50.00 1st Qu.: 50.00
## Median : 50.00 Median : 50.00 Median : 50.00 Median : 50.00
## Mean : 43.59 Mean : 44.94 Mean : 57.56 Mean : 50.95
## 3rd Qu.: 60.00 3rd Qu.: 50.00 3rd Qu.: 80.00 3rd Qu.: 60.00
## Max. :100.00 Max. :100.00 Max. :100.00 Max. :100.00
## Char_CausePassion_2
## Min. : 0.00
## 1st Qu.: 30.00
## Median : 50.00
## Mean : 46.11
## 3rd Qu.: 50.00
## Max. :100.00Norms Decisions
Norm_C <- data %>%
select( Norm_Community_2, Norm_Caste_2, Norm_Country_2 ,Norm_Ideology_2,
Norm_Religion_2, Norm_Generation_2, Norm_Species_2, Norm_CausPriority_2,
Norm_CausePassion_2)
summary(Norm_C)## Norm_Community_2 Norm_Caste_2 Norm_Country_2 Norm_Ideology_2
## Min. : 0.00 Min. : 0.00 Min. : 0.00 Min. : 0.0
## 1st Qu.: 40.00 1st Qu.: 35.00 1st Qu.: 10.00 1st Qu.: 50.0
## Median : 50.00 Median : 50.00 Median : 50.00 Median : 50.0
## Mean : 50.95 Mean : 48.07 Mean : 40.47 Mean : 54.1
## 3rd Qu.: 60.00 3rd Qu.: 60.00 3rd Qu.: 50.00 3rd Qu.: 60.0
## Max. :100.00 Max. :100.00 Max. :100.00 Max. :100.0
## Norm_Religion_2 Norm_Generation_2 Norm_Species_2 Norm_CausPriority_2
## Min. : 0.00 Min. : 0.00 Min. : 0.00 Min. : 0.00
## 1st Qu.: 20.00 1st Qu.: 20.00 1st Qu.: 50.00 1st Qu.: 50.00
## Median : 50.00 Median : 50.00 Median : 50.00 Median : 50.00
## Mean : 43.18 Mean : 44.04 Mean : 55.82 Mean : 51.37
## 3rd Qu.: 50.00 3rd Qu.: 50.00 3rd Qu.: 70.00 3rd Qu.: 60.00
## Max. :100.00 Max. :100.00 Max. :100.00 Max. :100.00
## Norm_CausePassion_2
## Min. : 0.00
## 1st Qu.: 22.50
## Median : 50.00
## Mean : 44.21
## 3rd Qu.: 50.00
## Max. :100.00Graphing EA decisions
Personal Decisions
Norms Decisions
Average giving
Amount_given <- data.frame(
name= c("Personal Donation", "Norms Donation"),
mean= c(mean(data$Char_Generosity, na.rm=TRUE),mean(data$N_Generosity2, na.rm=TRUE)),
sd=c(sd(data$Char_Generosity, na.rm=TRUE), sd(data$N_Generosity2, na.rm=TRUE) ))
Amount_given %>%
mutate(Percentage_Given = mean/50) %>%
mutate(se = sd/sqrt(311)) %>%
mutate(me =qt(0.975,df=311-1)*se) -> Amount_given
Amount_given %>%
ggplot() + geom_bar(aes(x = name, y = Percentage_Given), stat = "identity", fill = "steelblue4", alpha=0.9, width = 0.5) + ylim(0, 100) +
geom_errorbar( aes(x=name, ymin=Percentage_Given-me, ymax=Percentage_Given+me), width=0.4, colour="black", alpha=0.9, size=0.4) +
labs(title = "Generosity Measure",
subtitle = "What percentage of the INR 5000 amount do people give?",
y= "Average Amount in Percentage",
x="") +
geom_text(aes(label = Percentage_Given, x = name, y = Percentage_Given), vjust = -0.8) +
theme_hc() +
theme(axis.title = element_text())
T-tests
Community_t <- t.test(data$Char_Community_2,data$Norm_Community_2, paired = TRUE)
Caste_t <-t.test(data$Char_Caste._2, data$Norm_Caste_2, paired = TRUE)
Country_t <-t.test(data$Char_Country_2, data$Norm_Country_2, paired = TRUE)
Ideology_t <- t.test(data$Char_Ideology_2, data$Norm_Ideology_2, paired= TRUE)
Religion_t <-t.test(data$Char_Religion_2, data$Norm_Religion_2, paired = TRUE)
Generation_t <-t.test(data$Char_Generation_2, data$Norm_Generation_2, paired = TRUE)
Species_t <-t.test(data$Char_Species_2, data$Norm_Species_2, paired = TRUE)
Cause_Priority_t <-t.test(data$Char_CausePriority_2, data$Norm_CausPriority_2, paired = TRUE)
Cause_Passion_t <-t.test(data$Char_CausePassion_2, data$Norm_CausePassion_2, paired = TRUE)
tab_ttests <- map_df(list(Community_t, Caste_t,Country_t, Religion_t, Ideology_t, Generation_t, Species_t, Cause_Priority_t, Cause_Passion_t), tidy)
tab_ttests[c("estimate", "statistic", "p.value")]## # A tibble: 9 x 3
## estimate statistic p.value
## <dbl> <dbl> <dbl>
## 1 1.56 1.09 0.276
## 2 -1.99 -1.59 0.114
## 3 0.836 0.633 0.527
## 4 0.402 0.349 0.727
## 5 -0.119 -0.0942 0.925
## 6 0.900 0.768 0.443
## 7 1.74 1.48 0.141
## 8 -0.421 -0.382 0.702
## 9 1.90 1.45 0.148tab_ttests## # A tibble: 9 x 8
## estimate statistic p.value parameter conf.low conf.high method alternative
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <chr> <chr>
## 1 1.56 1.09 0.276 310 -1.25 4.37 Paired t-~ two.sided
## 2 -1.99 -1.59 0.114 310 -4.47 0.478 Paired t-~ two.sided
## 3 0.836 0.633 0.527 310 -1.76 3.44 Paired t-~ two.sided
## 4 0.402 0.349 0.727 310 -1.86 2.67 Paired t-~ two.sided
## 5 -0.119 -0.0942 0.925 310 -2.61 2.37 Paired t-~ two.sided
## 6 0.900 0.768 0.443 310 -1.41 3.21 Paired t-~ two.sided
## 7 1.74 1.48 0.141 310 -0.579 4.05 Paired t-~ two.sided
## 8 -0.421 -0.382 0.702 310 -2.59 1.75 Paired t-~ two.sided
## 9 1.90 1.45 0.148 310 -0.680 4.47 Paired t-~ two.sided