Given the following criteria:

[tex]$00-04$[/tex] = package not delivered on time
[tex]$05-99$[/tex] = package delivered on time

Here is a portion of a random number table:

Table of Random Digits
\begin{tabular}{|l|l|l|l|l|l|l|}
\hline 1 & 31640 & 43402 & 96003 & 10498 & 01532 & 73869 \\
\hline 2 & 67940 & 85019 & 98036 & 98252 & 43838 & 45644 \\
\hline 3 & 21805 & 26727 & 73239 & 53929 & 42564 & 17080 \\
\hline
\end{tabular}

Beginning at line 1, and starting each new trial right after the previous trial, carry out 5 trials of this simulation. Based on the 5 trials, what proportion of the time can the shipping company expect to select more than 2 packages before finding one that was not delivered on time?

A. 0
B. 0.2
C. 0.4
D. 0.6



Answer :

To solve this problem, we need to go through the random digits provided, interpret them according to the given rules, and compute the proportion of trials where more than 2 packages were selected before finding a package that was not delivered on time.

### Step-by-Step Solution

1. Extract Random Digits:
- We have a table of random digits given in a list format.
- We start from the beginning and treat each 2-digit number as a package outcome.
- The packages are inspected sequentially.

2. Interpret Digits:
- If a 2-digit number is between 00-04, it indicates a package not delivered on time.
- If a 2-digit number is between 05-99, it indicates a package delivered on time.

3. Perform 5 Trials:
- Continue examining numbers until a not-delivered-on-time package is found.
- Count how many packages were checked before finding the not-delivered-on-time package.
- Stop after 5 trials.

4. Determine Proportion:
- Count how many of these trials required checking more than 2 packages before finding the not-delivered-on-time package.
- Compute the proportion of such trials out of the total number of trials (5 trials).

### Execution

Here's the approach broken down by the random digits available.

- Random Digits:
```
"31640", "43402", "96003", "10498", "01532", "73869",
"67940", "85019", "98036", "98252", "43838", "45644",
"21805", "26727", "73239", "53929", "42564", "17080"
```

- 5 Trials Extraction & Counting:
- Trial 1: 31, 64, 04 -> Found `not delivered on time` at 3rd position (2 packages delivered before this one).
- Trial 2: 34, 02 -> Found `not delivered on time` at 2nd position (1 package delivered before this one).
- Trial 3: 96, 00 -> Found `not delivered on time` at 2nd position (1 package delivered before this one).
- Trial 4: 10, 49, 80, 15 -> Found `not delivered on time` at 4th position (3 packages delivered before this one).
- Trial 5: 32, 73, 86, 94, 08 -> Found `not delivered on time` at 5th position (4 packages delivered before this one).

### Analysis of Results

- Packages checked more than twice:
- Trial 1: Checked 2 packages before `not delivered`.
- Trial 4: Checked 3 packages before `not delivered`.
- Trial 5: Checked 4 packages before `not delivered`.

- Proportion Calculation:
- Out of the 5 trials, 3 trials needed more than 2 packages to be checked.

### Conclusion

The proportion can be calculated as:
[tex]\[ \text{Proportion} = \frac{\text{Number of trials with more than 2 selections}}{\text{Total number of trials}} = \frac{3}{5} = 0.6 \][/tex]

Thus, the shipping company can expect that more than 2 packages will need to be checked before finding one that was not delivered on time, 60% of the time.

The correct answer is:
[tex]\[ \boxed{0.6} \][/tex]