the missing value will be -36 because if you multiplied it with 4 you will only have to add another -4 to get -144
Answer:
7/11
Step-by-step explanation:
Let X equal the decimal number
Equation 1:
X=0.63¯¯¯¯¯
With 2 digits in the repeating decimal group,
create a second equation by multiplying
both sides by 102 = 100
Equation 2:
100X=63.63¯¯¯¯¯
Subtract equation (1) from equation (2)
100XX99X===63.63...0.63...63
We get
99X=63
Solve for X
X=6399
Find the Greatest Common Factor (GCF) of 63 and 99, if it exists, and reduce the fraction by dividing both numerator and denominator by GCF = 9,
63÷999÷9=711
Therefore
X=711
In conclusion,
0.63¯¯¯¯¯=711
used
https://www.calculatorsoup.com/calculators/math/decimal-to-fraction-calculator.php
a) The linear function that models the population in t years after 2004 is: P(t) = -200t + 29600.
b) Using the function, the estimate for the population in 2020 is of 26,400.
<h3>What is a linear function?</h3>
A linear function is modeled by:
y = mx + b
In which:
- m is the slope, which is the rate of change, that is, by how much y changes when x changes by 1.
- b is the y-intercept, which is the value of y when x = 0, and can also be interpreted as the initial value of the function.
The initial population in 2004, of 29600, is the y-intercept. In 12 years, the population decayed 2400, hence the slope is:
m = -2400/12 = -200.
Hence the equation is:
P(t) = -200t + 29600.
2020 is 16 years after 2004, hence the estimate is:
P(16) = -200(16) + 29600 = 26,400.
More can be learned about linear functions at brainly.com/question/24808124
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Answer: D. To produce treatment groups with similar characteristics
Step-by-step explanation:
By using randomization in sampling, the Sample would be more representative of the Population it is based off of because different demographic characteristics may be picked.
This leads to a situation where the groups have similar characteristics between themselves thereby making it easier for comparison. For example, Group 1 would have certain types of people that will be represented in Group 2 and Group 3 as well. That way the effects of the drug can be properly studied as it affects different people. For instance, say there are 4 obese people in a sample of 10, instead of group one having all obese people, randomization may be able to give group one, 2 obese people and 2 obese people to group 2 as well. That way when comparing, the effects of the drug on the two groups is easier to be compared because the two groups have similar people.
