Difference between revisions of "TU Wien:Statistik und Wahrscheinlichkeitstheorie UE (Bura)/Übungen 2019W/8.2"

From VoWi
Jump to navigation Jump to search
m
Line 5: Line 5:
 
:(c) Compare your result to the output of <code>t.test()</code>
 
:(c) Compare your result to the output of <code>t.test()</code>
  
{{ungelöst}}
+
== Lösungsvorschlag==
 +
 
 +
a)
 +
 
 +
<syntaxhighlight lang=r>
 +
load('waitingtimes2.Rdata')
 +
par(mfrow=c(2,1))
 +
hist(unlist(wt[1]))
 +
hist(unlist(wt[2]))
 +
</syntaxhighlight>
 +
 
 +
b) TBD
 +
 
 +
c) TBD

Revision as of 09:11, 3 December 2019

Two-sample t-test using normal approximation

Messages are frequently sent from a sender to either receiver 1 or receiver 2. For both receivers, several times for the transfer were measured (in seconds) and stored in the file waitingtimes2.Rdata.

(a) Plot both data sets. Is their distribution approximately bell-shaped?
(b) Test the null-hypothesis of equal mean transfer times for both receivers on the 1%-level with a two sample t-test (using the normal approximation).
(c) Compare your result to the output of t.test()

Lösungsvorschlag

a)

load('waitingtimes2.Rdata')
par(mfrow=c(2,1))
hist(unlist(wt[1]))
hist(unlist(wt[2]))

b) TBD

c) TBD