One condition for deadlocks is the circular-wait condition. One way to ensure that this condition never holds is to impose a total ordering of all resource types and to require that each process requests resources in increasing order of enumeration. Given an example of a bank transaction, is deadlock possible for this case

Explanation:

Let us understand the term "Dead lock"

A deadlock is a situation where whole set of process is locked, since each of the process is waiting or holding the resource of another process. Each process will be interdependent and waiting for the same resource.

Deadlock is possible during bank transaction in the following situation:

A & B are two accounts where A tries to transfer funds to B and B tries to transfer fund to A.

When both tries to transfer funds at the same time, deadlock occurs.

A deadlock can be avoided by any one of the four methods.

They are: Mutual exclusion, No preemption, circular wait, hold and wait.

A deadlock refers to a situation in which two computer program that shares the same resource/data  are  preventing each other from accessing the resource/data , resulting in both programs ceasing to function.

Explanation:

A deadlock refers to a situation in which  the whole  process is locked, since each of the process is waiting or holding the resource of another process. The two process are interdependent on each other and cannot function independently

An example of Deadlock occurring  during a bank transaction is  

Lets consider two bank accounts of customer X & Customer Y

Now if  customer X  tries to transfer funds to Customer Y or Y tries to transfer fund to X ,when these 2 process occur simultaneously at the same time a deadlock is said to have occur

0.95; September.

Step-by-step explanation:

In a graphing calculator, we enter the data.  The low temperature will be entered as the independent variable and the high temperature will be entered as the dependent.

Running a linear regression on the data, we get a correlation coefficient, r, of 0.94775 ≈ 0.95.

Since the correlation coefficient for October is 0.89, while that of September is 0.95, the correlation for September is stronger than that of October.  The closer the correlation coefficient is to 1, the stronger the relationship.