An experiment consists of tossing a nickel, a dime and a quarter. Of interest is the side the coin lands on.
List the sample space.
Let
$A$ be the event that there are at least two tails. Find
$\text{P(A)}$ .
Let
$B$ be the event that the first and second tosses land on heads. Are the events
$A$ and
$B$ mutually exclusive? Explain your answer in 1 - 3 complete sentences, including justification.
Rewrite the basic Addition Rule
$\text{P(Y OR Z)}=\mathrm{P(Y)}+\mathrm{P(Z)}-\mathrm{P(YANDZ)}$ using the information that Y and Z are independent events.
Use the rewritten rule to find
$\mathrm{P(Z)}$ if
$\mathrm{P(YORZ)}=0.71$ and
$\mathrm{P(Y)}=0.42$ .
The following are real data from Santa Clara County, CA. As of a certain time, there had been a total of 3059 documented cases of AIDS in the county. They were grouped into the following categories (
Source: Santa Clara County Public H.D. ):
* includes homosexual/bisexual IV drug users
Homosexual/Bisexual
IV Drug User*
Heterosexual Contact
Other
Totals
Female
0
70
136
49
____
Male
2146
463
60
135
____
Totals
____
____
____
____
____
Suppose one of the persons with AIDS in Santa Clara County is randomly selected. Compute the following:
$\text{P(person is female)}$ =
$\text{P(person has a risk factor Heterosexual Contact)}$ =
$\text{P(person is female OR has a risk factor of IV Drug User)}$ =
$\text{P(person is female AND has a risk factor of Homosexual/Bisexual)}$ =
$\text{P(person is male AND has a risk factor of IV Drug User)}$ =
$\text{P(female GIVEN person got the disease from heterosexual contact)}$ =
Construct a Venn Diagram. Make one group females and the other group heterosexual contact.
Solve these questions using probability rules. Do NOT use the contingency table above. 3059 cases of AIDS had been reported in Santa Clara County, CA, through a certain date. Those cases will be our population. Of those cases, 6.4% obtained the disease through heterosexual contact and 7.4% are female. Out of the females with the disease, 53.3% got the disease from heterosexual contact.
$\text{P(person is female) =}$
$\text{P(person obtained the disease through heterosexual contact) =}$
$\text{P(female GIVEN person got the disease from heterosexual contact) =}$
Construct a Venn Diagram. Make one group females and the other group heterosexual contact. Fill in all values as probabilities.
In this morden time nanotechnology used in many field .
1-Electronics-manufacturad IC ,RAM,MRAM,solar panel etc
2-Helth and Medical-Nanomedicine,Drug Dilivery for cancer treatment etc
3- Atomobile -MEMS, Coating on car etc.
and may other field for details you can check at Google
Azam
anybody can imagine what will be happen after 100 years from now in nano tech world
Prasenjit
after 100 year this will be not nanotechnology maybe this technology name will be change .
maybe aftet 100 year . we work on electron lable practically about its properties and behaviour by the different instruments
Azam
name doesn't matter , whatever it will be change... I'm taking about effect on circumstances of the microscopic world
Prasenjit
how hard could it be to apply nanotechnology against viral infections such HIV or Ebola?
Damian
silver nanoparticles could handle the job?
Damian
not now but maybe in future only AgNP maybe any other nanomaterials
Azam
Hello
Uday
I'm interested in Nanotube
Uday
this technology will not going on for the long time , so I'm thinking about femtotechnology 10^-15
Prasenjit
can nanotechnology change the direction of the face of the world
At high concentrations (>0.01 M), the relation between absorptivity coefficient and absorbance is no longer linear. This is due to the electrostatic interactions between the quantum dots in close proximity. If the concentration of the solution is high, another effect that is seen is the scattering of light from the large number of quantum dots. This assumption only works at low concentrations of the analyte. Presence of stray light.
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1 It is estimated that 30% of all drivers have some kind of medical aid in South Africa. What is the probability that in a sample of 10 drivers: 3.1.1 Exactly 4 will have a medical aid. (8) 3.1.2 At least 2 will have a medical aid. (8) 3.1.3 More than 9 will have a medical aid.