12. Which three correlation coefficents have a strong linear correlation.

When they invest K dollars, a fishery can produce Q(K) pounds of fish per month, where Q(K) = 111 K1/3. In t months from now, th

Vedmedyk [2.9K]

Answer:

a) The rate of production of fishers per month is changing with time at a rate of 40.5 in 4 months from the start of operations.

b) In 4 months from now, the fisher's production will be 1081.53 pounds of fishes per month.

Step-by-step explanation:

The calculation is presented in the attached images to this solution.

4 0

3 years ago

Pls help i dont wanna ruin my sleep schedule

nata0808 [166]

3) MD=ED
MJD=EVD
JD=VD
TriangleMJD=TriangleEVD
by SAS

4) BE=AE
ER=ER
BR=AR
TriangleBER=TriangleAER
by SSS

7 0

3 years ago

Compare the difference between an independent event and a dependent event.

pshichka [43]

<h2>⚠ANSWER⚠ </h2>

Dependent event is when two events are dependent events, one event influences the probability of another event whereas independent event has no effect on the probability of another event occurring.

↪DEPENDENT EVENT

When two events are dependent events, one event influences the probability of another event. A dependent event is an event that relies on another event to happen first. Dependent events in probability are no different from dependent events in real life. If you want to attend a concert, it might depend on whether you get overtime at work. if you want to visit family out of the country next month, it depends on whether or not you can get a passport in time. More formally, we say that when two events are dependent, the occurrence of one event influences the probability of another event.

Simple examples of dependent events

Robbing a bank and going to jail.
Not paying your power bill on time and having your power cut off.
Boarding a plane first and finding a good seat.
Parking illegally and getting a parking ticket.

↪INDEPENDENT EVENT

An independent event is an event that has no connection to another event’s chances of happening (or not happening). In other words, the event has no effect on the probability of another event occurring. Independent events in probability are no different from independent events in real life. Where you work has no effect on what color car you drive. Buying a lottery ticket has no effect on having a child with blue eyes.

When two events are independent, one event does not influence the probability of another event.

Simple examples of independent events