The connector for ethernet cables is called RJ45. for phone jack is RJ11. Although they look the same, the RJ11 has only 4 leads, as opposed to 9 leads in RJ45. Also, RJ11 is not as wide as RJ45, so the connector does not fit.
Even if it would, the signals would be totally incompatible, so no success can be expected.
Answer:
To make the group of four we can write 100011 as 00100011
Now, the two groups are:- 0010 and 0011
And 0010 in binary corresponds to 3 in Hexadecimal
And 0011 in binary corresponds to 4 in Hexadecimal.
So, 100011 of binary corresponds to 34 of hex.
Answer:
Check the explanation
Explanation:
use `my_guitar_shop`;
#delete the procedure test if it exists.
DROP PROCEDURE IF EXISTS test;
DELIMITER //
CREATE PROCEDURE test ()
BEGIN
#declare variable sqlerr to store if there is an sql exception
declare sqlerr tinyint default false;
#declare variable handler to flag when duplicate value is inserted
declare continue handler for 1062 set sqlerr = TRUE;
#start transaction
start transaction;
delete from order_items where order_id in
(select order_id from orders where customer_id=6);
delete from orders where customer_id=6;
delete from addresses where customer_id=6;
delete from customers where customer_id=6;
if sqlerr=FALSE then
commit;
select 'Transaction Committed' as msg;
else
rollback;
select 'Transaction rollbacked' as msg;
end if;
end //
delimiter ;
call test();
Answer:
Two examples of processes for data collection are:
In-person interviewing: This is a face-to-face method or process of data collection. It has a high rate of response and allows you to ask follow-up questions when the response of the interviewee is not clear.
Sample Surveys: In this method, a sample is selected from a large population and then a questionnaire is constructed and sent to the sample for them to give their feedback or response in line with the research problem.
Three Key Principles considered in these processes to ensure data accuracy are:
Completeness: This means that what was expected to be collected as data was what was collected. Completeness of data is a vital factor for data quality.
Consistency: There must be uniformity in the data collection process. Everyone involved in the data collection process must understand what is required of them.
Accuracy: The data must be free of errors
Explanation:
