Differences

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--- summary_of_hypothesis_testing:output01 [2025/11/30 22:44] – hkimscil
+++ summary_of_hypothesis_testing:output01 [2025/11/30 22:50] (current) – hkimscil
@@ Line 61: / Line 61: @@
 > diff <- m.treated.s-mean(p1)
 > diff/se.z1
-[1] 0.1983834
+[1] 0.5253907
 > zscore <- abs(diff/se.z1)
 > pnorm(zscore, lower.tail = F)*2
-[1] 0.8427451
+[1] 0.5993116
 > tscore <- zscore
 > pt(tscore, df=n.s-1, lower.tail = F)*2
-[1] 0.844416
+[1] 0.6041323
 >
 > # usual way - using sample's variance
@@ Line 74: / Line 74: @@
 > se.s <- sqrt(var(treated.s)/n.s)
 > se.s
-[1] 1.900271
+[1] 1.83652
 > tscore <- diff/se.s
 > tscore
-[1] 0.2087948
+[1] 0.572159
 >
 >
@@ Line 110: / Line 110: @@
 > abline(v=m.treated.s, col='red', lwd=3)
 > se.s
-[1] 1.900271
+[1] 1.83652
 > se.z1
 [1] 2
 >
 > c(m.treated.s-2*se.s, m.treated.s+2*se.s)
-[1]  96.59622 104.19731
+[1]  97.37774 104.72382
 > c <- qt(0.975, n.s-1)
 > c
 [1] 2.063899
 > c(m.treated.s-c*se.s, m.treated.s+c*se.s)
-[1]  96.4748 104.3187
+[1]  97.26039 104.84117
 > m.p2
 [1] 104
@@ Line 144: / Line 144: @@
 > tscore <- abs(diff/se.s)
 > pt(tscore, df=n.s-1, lower.tail = F) * 2
-[1] 0.8363704
+[1] 0.5725352
 > t.test(treated.s, mu=m.p1, var.equal = T)
@@ Line 150: / Line 150: @@
 data:  treated.s
-t = 0.20879, df = 24, p-value = 0.8364
+t = 0.57216, df = 24, p-value = 0.5725
 alternative hypothesis: true mean is not equal to 100
 percent confidence interval:
-.4748 104.3187
+.26039 104.84117
 sample estimates:
 mean of x
-.3968
+.0508
 >
 </code>
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