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

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:(c) Compare your result to the output of <code>t.test()</code> | :(c) Compare your result to the output of <code>t.test()</code> | ||

== 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 10:11, 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