diff --git a/Connect Project R Markdown.Rmd b/Connect Project R Markdown.Rmd
index ecb4bff..7a89256 100644
--- a/Connect Project R Markdown.Rmd	
+++ b/Connect Project R Markdown.Rmd	
@@ -270,18 +270,41 @@ head(Q13_data)
   # then analyze based on specific one
 Q13_data$Q13_recode <- factor(Q13_data$Q13_recode, levels = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10), labels = c("Church of England", "Roman Catholic", "Methodist", "Other Christian", "Jewish", "Muslim", "Sikh", "Hindu", "Multi-Faith", "None of the above"))
 
+# Test with only included levels
+Q13_data$Q13_recode <- factor(Q13_data$Q13_recode, levels = c(1, 2, 4, 6), labels = c("Church of England", "Roman Catholic", "Other Christian", "Muslim"))
+# No change with this one...still nonsignificant difference
+
   # Q22
 hist(Q13_data$Q22_average)
 specific_affiliation_test <- aov(Q22_average ~ Q13_recode, data = Q13_data)
+typeof(Q13_data$Q13_recode)
 summary(specific_affiliation_test)
 
   # Q23
+specific_affiliation_test_Q23 <- manova(cbind(Q23_1, Q23_2) ~ Q13_recode, data = Q13_data)
+summary(specific_affiliation_test_Q23)
 
   # Q27
+specific_affiliation_test_Q27 <- manova(cbind(Q27_1, Q27_2, Q27_3, Q27_4, Q27_5, Q27_6, Q27_7) ~ Q13_recode, data = Q13_data)
+summary(specific_affiliation_test_Q27)
 
 ## Q15-16 with Q22, Q23, Q27
   # Q15 is binary; 1st test whether difference in answers based on whether the school has an informal religious character or not. Q16 provides further detail and can be explored
 
+religion_affiliation_data$Q15 <- factor(religion_affiliation_data$Q15, levels = c("No", "Yes"), labels = c("No", "Yes"))
+
+  ## Q22
+informal_affiliation_test_Q22 <- t.test(Q22_average ~ Q15, data = religion_affiliation_data, paired = FALSE)
+informal_affiliation_test_Q22
+
+  ## Q23
+informal_affiliation_test_Q23 <- manova(cbind(Q23_1, Q23_2) ~ Q15, data = religion_affiliation_data)
+summary(informal_affiliation_test_Q23)
+
+  ## Q27
+informal_affiliation_test_Q27 <- manova(cbind(Q27_1, Q27_2, Q27_3, Q27_4, Q27_5, Q27_6, Q27_7) ~ Q15, data = religion_affiliation_data)
+summary(informal_affiliation_test_Q27)
+
 
 ## Q21 with Q22, Q23, Q27
   # Q21 is personal religious affiliation. This may be more tricky as it is a free answer...but can code the type of religious affiliation and test that way? -- would be chi-square or some sort of non-para analysis due to the small number of respondents who answered this