Answer:
0.3101001000......
0.410100100010000....
Step-by-step explanation:
To find irrational number between any two numbers, we first need to understand what a rational and irrational number is.
Rational number is any number that can be expressed in fraction of form
. Since q can be 1, all numbers that terminate are rational numbers. Example: 1, 12.34, 123.66663
Irrational number on the other hand can't be expressed as a fraction and do not terminate. Also, there is no pattern in numbers i.e. there is no repetition in numbers after the decimal point.
For example: 3.44444..... can be expressed as rational number 3.45.
But 3.414114111.... is an irrational number as there no pattern observed. Also,it does not terminate.
We can find infinite number of irrational numbers in between two rational numbers.
<u>Irrational numbers in between 0.3 and 0.7:</u>
0.3101001000......
0.410100100010000....
0.51010010001.......
0.6101001000....
There are many others. We can choose any two as answers.
Answer:
If f(x) = 3x, this means that any number that replaces x in the parenthesis, would replace x in the right side too.
When x = -1:
f(-1) = 3(-1) = -3
When x = 0:
f(0) = 3(0) = 0
When x = 3:
f(3) = 3(3) = 9
~
Answer:
should be 0.28125
Step-by-step explanation:
Answer:
Sampling distribution
Step-by-step explanation:
The sampling distribution of a sample statistic is the probability distribution of the population of all possible values of the sample statistic.
Answer:
(a) 0.85
(b) 0.7225
Step-by-step explanation:
(a) The point estimate for the proportion of all such components that are not defective is given by the number of non-defective units in the sample divided by the sample size:

The proportion is 0.85.
(b) Assuming that the sample is large enough to accurately provide a point estimate for the whole population, this can be treated as a binomial model with probability of success (non-defective part) p = 0.85. Since both components must be non-defective for the system to work, the probability of two successes in two trials is:

An estimate of 0.7225 for the proportion of all such systems that will function properly.