setwd("~/Documents/Dropbox/Research/Adrian")
d<-read.csv ("AI_conservatism_risk_new_study_1.csv", header=T, sep=",")
table(d$Q34)
##
## attention 23 24 26 27
## 1 1 1 3 1 4
## 28 29 30 32 33 34
## 1 2 1 1 1 1
## 35 37 39 40 attention Attention
## 2 2 1 1 257 3
## ATTENTION attention
## 2 14
#d<-subset(d, Q34=="attention" | Q34=="Attention" | Q34=="attention " | Q34 == " attention" | Q34 == "ATTENTION")
STUDY 1
d$socialconservatism<-d$Q16_2
cor.test(d$socialconservatism, d$comfort_society_1)
##
## Pearson's product-moment correlation
##
## data: d$socialconservatism and d$comfort_society_1
## t = 1.1037, df = 99, p-value = 0.2724
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.08706052 0.29924582
## sample estimates:
## cor
## 0.1102547
cor.test(d$socialconservatism, d$comfort_self_1)
##
## Pearson's product-moment correlation
##
## data: d$socialconservatism and d$comfort_self_1
## t = 1.2334, df = 99, p-value = 0.2204
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.07420591 0.31097999
## sample estimates:
## cor
## 0.1230174
cor.test(d$socialconservatism, d$gen_risk_1)
##
## Pearson's product-moment correlation
##
## data: d$socialconservatism and d$gen_risk_1
## t = -0.60615, df = 99, p-value = 0.5458
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.2532376 0.1362506
## sample estimates:
## cor
## -0.06080789
cor.test(d$socialconservatism, d$threat_lives_1)
##
## Pearson's product-moment correlation
##
## data: d$socialconservatism and d$threat_lives_1
## t = -0.064244, df = 99, p-value = 0.9489
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.2016414 0.1892214
## sample estimates:
## cor
## -0.00645662
cor.test(d$socialconservatism, d$threat_jobs_1)
##
## Pearson's product-moment correlation
##
## data: d$socialconservatism and d$threat_jobs_1
## t = 1.177, df = 99, p-value = 0.242
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.07979473 0.30589269
## sample estimates:
## cor
## 0.1174766
d$conservatism<-d$Q16_1
cor.test(d$conservatism, d$comfort_society_1)
##
## Pearson's product-moment correlation
##
## data: d$conservatism and d$comfort_society_1
## t = 0.77874, df = 99, p-value = 0.438
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.1192300 0.2693591
## sample estimates:
## cor
## 0.07802749
cor.test(d$conservatism, d$comfort_self_1)
##
## Pearson's product-moment correlation
##
## data: d$conservatism and d$comfort_self_1
## t = 0.94454, df = 99, p-value = 0.3472
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.1028341 0.2846857
## sample estimates:
## cor
## 0.09450453
cor.test(d$conservatism, d$gen_risk_1)
##
## Pearson's product-moment correlation
##
## data: d$conservatism and d$gen_risk_1
## t = -0.72617, df = 99, p-value = 0.4694
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.2644661 0.1244202
## sample estimates:
## cor
## -0.07278907
cor.test(d$conservatism, d$threat_lives_1)
##
## Pearson's product-moment correlation
##
## data: d$conservatism and d$threat_lives_1
## t = -0.18544, df = 99, p-value = 0.8533
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.2132971 0.1774509
## sample estimates:
## cor
## -0.01863467
cor.test(d$conservatism, d$threat_jobs_1)
##
## Pearson's product-moment correlation
##
## data: d$conservatism and d$threat_jobs_1
## t = 1.1724, df = 99, p-value = 0.2438
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.08025213 0.30547536
## sample estimates:
## cor
## 0.1170226
STUDY 3
names(d)
## [1] "v1" "V2" "V3"
## [4] "V4" "V5" "V6"
## [7] "V7" "V8" "V9"
## [10] "V10" "Q26" "Q28"
## [13] "Q30" "Q34" "Description_general"
## [16] "comfort_society_1" "comfort_self_1" "gen_risk_1"
## [19] "threat_lives_1" "threat_jobs_1" "joke_trust_1"
## [22] "joke_risk_1" "car_trust_1" "car_risk_1"
## [25] "Q8" "Q10" "Q12"
## [28] "Q14" "Q16_1" "Q16_2"
## [31] "Q16_3" "LocationLatitude" "LocationLongitude"
## [34] "LocationAccuracy" "socialconservatism" "conservatism"
cor.test(d$socialconservatism, d$joke_trust_1)
##
## Pearson's product-moment correlation
##
## data: d$socialconservatism and d$joke_trust_1
## t = -1.7599, df = 97, p-value = 0.08158
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.36078684 0.02228209
## sample estimates:
## cor
## -0.1759035
cor.test(d$socialconservatism, d$joke_risk_1)
##
## Pearson's product-moment correlation
##
## data: d$socialconservatism and d$joke_risk_1
## t = -0.72857, df = 97, p-value = 0.468
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.2672926 0.1254655
## sample estimates:
## cor
## -0.07377359
cor.test(d$socialconservatism, d$car_trust_1)
##
## Pearson's product-moment correlation
##
## data: d$socialconservatism and d$car_trust_1
## t = 2.1012, df = 97, p-value = 0.03821
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.01172093 0.38999780
## sample estimates:
## cor
## 0.20865
cor.test(d$socialconservatism, d$car_risk_1)
##
## Pearson's product-moment correlation
##
## data: d$socialconservatism and d$car_risk_1
## t = -2.3557, df = 97, p-value = 0.0205
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.41115001 -0.03690167
## sample estimates:
## cor
## -0.2326189