Answer:
100,000,000,009,099,998,878,374
Step-by-step explanation:
Using the fundamental counting theorem, we have that:
- 648 different area codes are possible with this rule.
- There are 6,480,000,000 possible 10-digit phone numbers.
- The amount of possible phone numbers is greater than 400,000,000, thus, there are enough possible phone numbers.
The fundamental counting principle states that if there are p ways to do a thing, and q ways to do another thing, and these two things are independent, there are ways to do both things.
For the area code:
- 8 options for the first digit.
- 9 options for the second and third.
Thus:
648 different area codes are possible with this rule.
For the number of 10-digit phone numbers:
- 7 digits, each with 10 options.
- 648 different area codes.
Then
There are 6,480,000,000 possible 10-digit phone numbers.
The amount of possible phone numbers is greater than 400,000,000, thus, there are enough possible phone numbers.
A similar problem is given at brainly.com/question/24067651
In order the numbers are 20, 29, 32, 37, 42.
So that means the median is 32. In order for the median to stay the same one of the three data values must be 32 as well as adding a number to each side of the ends. One 32 or less another 32or more.
The mean right now is: 20+29+32+37+42=160 and there are 5 values.
Mean: 160/5=32
For it to increase by 10 it has to be 42.
extra 3 numbers I used were 31, 32, & 113 (those are your answer)
2x6=12
3x6=18
12+18=22
2x3=6
2x6=12
6+12=18
Answer:
b. I and II are both false.
Step-by-step explanation:
I. For a significance level, the two tailed hypothesis is not always accurate than the one tailed hypothesis test. The hypothesis testing is carried to find out the correctness of a claim of a population parameter. The two tail hypothesis test which used both positive and negative tails of the distribution is not always more accurate than one tailed test.
II. The process of the point estimation involves the utilization of the values of a statistic which is obtained from the sample data to obtain the best estimate of a corresponding unknown parameter in the given population.
Hence, both the statements are false.
