The answer to this problem is x> -64
The phase of inferential statistics which is sometimes considered to be the most crucial because errors in this phase are the most difficult to correct is "data gathering".
<h3>What is
inferential statistics?</h3>
Inferential statistics are frequently employed to compare treatment group differences.
Some characteristics of inferential statistics are-
- Inferential statistics compare treatments groups and make conclusions about the greater population of participants using measures from the experiment's sample of subjects.
- Inferential statistics aids in the development of explanations for a condition or phenomenon.
- It enables you to draw conclusions on extrapolations, which distinguishes it from descriptive statistics, which simply summarize the information that has been measured.
- There are numerous varieties of inferential statistics, each with its own set of research design & sample characteristics.
- To select the correct statistical test of their experiment, researchers should reference the numerous texts about experimental design and statistics.
To know more about the inferential statistics, here
brainly.com/question/4774586
#SPJ4
Answer:
I really hope it will help you....
Step-by-step explanation:
Answer1-we can see that in last two hours the line is downwards so we can easily proof or see that at 11th and 12th are the temperature is lowest.
Answer2-in second one we can see that in hour 1,2,3,4 the temperature has kept on increasing.
Answer 3- between three or four temperature of increasing.
Answer:
number c
Step-by-step explanation:
4 x 5 = 20
4x 8 = 32
5 x 5 = 32
5 x 8 = 40
Hope this helps ;)
Answer:
a) P(X∩Y) = 0.2
b) 
= 0.16
c) P = 0.47
Step-by-step explanation:
Let's call X the event that the motorist must stop at the first signal and Y the event that the motorist must stop at the second signal.
So, P(X) = 0.36, P(Y) = 0.51 and P(X∪Y) = 0.67
Then, the probability P(X∩Y) that the motorist must stop at both signal can be calculated as:
P(X∩Y) = P(X) + P(Y) - P(X∪Y)
P(X∩Y) = 0.36 + 0.51 - 0.67
P(X∩Y) = 0.2
On the other hand, the probability that he must stop at the first signal but not at the second one can be calculated as:
= P(X) - P(X∩Y)
= 0.36 - 0.2 = 0.16
At the same way, the probability 
that he must stop at the second signal but not at the first one can be calculated as:
= P(Y) - P(X∩Y)
= 0.51 - 0.2 = 0.31
So, the probability that he must stop at exactly one signal is:
