Answer:
Step-by-step explanation:
Just so you know, for your information, composite numbers have more than <em>two</em> factors, and prime numbers have EXACTLY two factors [1 and itself (that number)].
* A common mistake is that people make is that they say that all even numbers are composite, and that is false because there are odd numbers that are PERFECT SQUARES and can be divided evenly without leaving a remainder. So, using the Prime Factorization Method, you can do this in two structures:
- Ladder Diagram
- Factor Tree
Factor Tree
85
/ \
17 5
Ladder Diagram
17|<u>85</u>
5|<u>5</u>
1
In the Ladder Diagram, when you are down to 1, you know that factorization is over and there is nothing else to do.
So, with that being said, the prime factorization of 85 is 17 × 5.
I am joyous to assist you anytime.
First vector orthogonal<span> to ⟨−</span>3<span>,4</span>
Step-by-step explanation:
(x+5)^2 = 2( 5x-3)
x^2+25=10x-6
x^2-10x+25+6= 0
x^2-10x+31=0
a=1, b
Answer: 12.65 cm
Step-by-step explanation:
Use the Pythagoras theorem,
a^2 + b^2= c^2
You are given the hypotenuse , which is c and another leg which is either a or b, does not particularly matter- rearrange to find the missing length
c^2 - b^2 = a^2
14^2 - 6^2 = 160
Square root 160 to find the missing length
12.65
Hope this helped :)
Answer:
Step-by-step explanation:
Data given and notation
n=1000 represent the random sample taken
estimated proportion of residents that favored the annexation
is the value that we want to test
z would represent the statistic (variable of interest)
represent the p value (variable of interest)
Concepts and formulas to use
We need to conduct a hypothesis in order to test the claim that the true proportion is higher than 0.5:
Null hypothesis:
Alternative hypothesis:
When we conduct a proportion test we need to use the z statistic, and the is given by:
(1)
The One-Sample Proportion Test is used to assess whether a population proportion 
is significantly different from a hypothesized value 
.
Calculate the statistic
Since we have all the info required we can replace in formula (1) like this:
Statistical decision
It's important to refresh the p value method or p value approach . "This method is about determining "likely" or "unlikely" by determining the probability assuming the null hypothesis were true of observing a more extreme test statistic in the direction of the alternative hypothesis than the one observed". Or in other words is just a method to have an statistical decision to fail to reject or reject the null hypothesis.
The next step would be calculate the p value for this test.
Since is a right tailed test the p value would be:
