Rule-based vs neural-based

# Define the data
earlier_mt <- c(0.0853185310821577, 0.10307998012916053, 0.13989835700362022, 0.04535495247569559, 
                0.0964681380347691, 0.09206007028318165, 0.5151311734372971, 0.04445890262415969, 
                0.13774908293752872, 0.09884708848732902, 0.21806459160581257, 0.08840558905158395, 
                0.1361649303722475, 0.10503471398230979)
google <- c(0.08605356769198584, 0.11223934018051673, 0.17478911679243345, 0.27606934245937204, 
            0.04578754578754587, 0.5960453388940018, 0.3023299276975748, 0.058826718716113724, 
            1.0, 0.6302069892080631, 0.2796656363180792, 0.059436274509803995, 0.48421439671439664, 
            0.1995604757483057)

# Test for normality using Shapiro-Wilk test
shapiro_earlier_mt <- shapiro.test(earlier_mt)
shapiro_google <- shapiro.test(google)

# Display results of Shapiro-Wilk Test
cat("Shapiro-Wilk Test Results:\n")
cat("Earlier MT: Statistic =", shapiro_earlier_mt$statistic, ", p-value =", shapiro_earlier_mt$p.value, "\n")
cat("Google: Statistic =", shapiro_google$statistic, ", p-value =", shapiro_google$p.value, "\n\n")

# Perform Wilcoxon Signed-Rank Test
wilcoxon_test <- wilcox.test(earlier_mt, google, paired = TRUE)

# Display Wilcoxon Signed-Rank Test results
cat("Wilcoxon Signed-Rank Test Results:\n")
cat("Statistic =", wilcoxon_test$statistic, ", p-value =", wilcoxon_test$p.value, "\n")