<span>2/15 if drawn without replacement.
1/9 if drawn with replacement.
Assuming that the chips are drawn without replacement, there are 6 * 5 different possibilities. And that's a low enough number to exhaustively enumerate them. So they are:
1,2 : 1,3 : 1,4 : 1,5 : 1,6
2,1 : 2,3 : 2,4 : 2,5 : 2,6
3,1 : 3,2 : 3.4 : 3,5 : 3,6
4,1 : 4,2 : 4.3 : 4,5 : 4,6
5,1 : 5,2 : 5.3 : 5,4 : 5,6
6,1 : 6,2 : 6.3 : 6,4 : 6,5
Of the above 30 possible draws, there are 4 that add up to 5. So the probability is 4/30 = 2/15
If the draw is done with replacement, then there are 36 possible draws. Once again, small enough to exhaustively list, they are:
1,1 : 1,2 : 1,3 : 1,4 : 1,5 : 1,6
2,1 : 2,2 : 2,3 : 2,4 : 2,5 : 2,6
3,1 : 3,2 : 3,3 : 3.4 : 3,5 : 3,6
4,1 : 4,2 : 4.3 : 4,4 : 4,5 : 4,6
5,1 : 5,2 : 5.3 : 5,4 : 5,5 : 5,6
6,1 : 6,2 : 6.3 : 6,4 : 6,5 : 6,6
And of the above 36 possibilities, exactly 4 add up to 5. So you have 4/36 = 1/9</span>
When the inventory is 4000 clocks, the prediction is that 3920 clocks will work.
Keisha will have more than 97% of the products working.
Step-by-step explanation:
These are three prediction that Keisha can make based on the report that said 6 of 300 clocks tested weren't working.
Base on that information, Keisha can calculate an experimental probability, dividing <em>clocks that don't work properly </em>by <em>the total amount of clocks</em><em>:</em>
<em></em>
Therefore, the probability of success is 100% - 2% = 98%.
This means that Keisha has a probability of having 98% of all clocks functioning properly. So, she can make the prediction:<em> from 4000 clocks, 3920 will work. </em>Also, she can predict that she will actually have more than 97% working, because the experimental probability is higher than that.