# 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