SOCR EduMaterials Activities More Examples

From SOCR
Revision as of 17:46, 8 July 2007 by Nchristo (talk | contribs)
Jump to: navigation, search

Example 1:

From a large shipment of peaches, 12 are selected for quality control. Suppose that in this particular shipment only \(65 \%\) of the peaches are unbruised. If among the 12 peaches 9 or more are unbruised the shipment is classified A. If between 5 and 8 are unbruised the shipment is classified B. If fewer than 5 are unbruised the shipment is classified C. Compute the probability that the shipment will be classified A, B, C.

We can use the formula and compute

\( P(A) = P(X \ge 9) = \sum_{x=9}^{12} {12 \choose x} 0.65^x 0.35^{12-x}=\cdots \)

\( P(B) = P(5 \le X \le 8) = \sum_{x=5}^{8} {12 \choose x} 0.65^x 0.35^{12-x}=\cdots \)

\( P(C) = P(X < 5) = \sum_{x=0}^{4} {12 \choose x} 0.65^x 0.35^{12-x}=\cdots \)

Or, much easier using SOCR...

Here is the distribution of the number of unbruised peaches among the 12 selected. After we enter \(n=12\) and \(p=0.65\) we get the distribution below:


Error creating thumbnail: File missing


Now, in the Left Cut Off and Right Cut Off boxes (bottom left corner of the applet) enter the numbers 5 and 8 respectively. What do you observe?


SOCR Activities More Examples Christou peaches2.jpg


The distribution is divided into three parts. The left part (less than 5), the right part (above 8), and the between part (between 5 and 8 included). All the SOCR distributions applets are designed in the same way. From the applet the probabilities are \( P(A)=0.346653, P(B)=0.627840, P(C)=0.025507.\)


Example 2:

Suppose a lot of size \(N\) is accepted if it contains no more than \(c\) defective components. A production manager selects at random a sample of \(n\) components from this lot and determines the number of defective components. If he finds more than \(c\) defective components then the lot is rejected, otherwise it is accepted. Answer the following questions:

a. Suppose the manager wants to choose between two lot sizes\[N=500\] or \(N=1000\). Both lots will contain \(1 \%\) defective components and he will sample in both cases \(n=5 \%\) of the lot. Which sampling scheme will have a higher probability of rejecting the lot if \(c=0\)? Use SOCR and print the two snapshots.

b. Repeat (a) with \(c=1\). Answer the question using SOCR.

c. Repeat (a) with \(c=1\) and defective rate \(10 \%\). Use SOCR.





Translate this page:

(default)
Uk flag.gif

Deutsch
De flag.gif

Español
Es flag.gif

Français
Fr flag.gif

Italiano
It flag.gif

Português
Pt flag.gif

日本語
Jp flag.gif

България
Bg flag.gif

الامارات العربية المتحدة
Ae flag.gif

Suomi
Fi flag.gif

इस भाषा में
In flag.gif

Norge
No flag.png

한국어
Kr flag.gif

中文
Cn flag.gif

繁体中文
Cn flag.gif

Русский
Ru flag.gif

Nederlands
Nl flag.gif

Ελληνικά
Gr flag.gif

Hrvatska
Hr flag.gif

Česká republika
Cz flag.gif

Danmark
Dk flag.gif

Polska
Pl flag.png

România
Ro flag.png

Sverige
Se flag.gif