2x2 + x −#6 _____________
x2 − 1
∙ x
__
2 + 2x + 1
x 2 − 4
Rewrite as multiplication.
(2x − 3)(x + 2) __
(x + 1)(x − 1) ∙ (x + 1)(x + 1) __ (x + 2)(x − 2) Factor the numerator and denominator.
(2x − 3)(x + 2)(x + 1)(x + 1) ___ (x + 1)(x − 1)(x + 2)(x − 2) Multiply numerators and denominators.
(2x − 3)(x + 2)(x + 1)(x + 1) ___ (x + 1)(x − 1)(x + 2)(x − 2) Cancel common factors to simplify.
(2x − 3)(x + 1) __ (x − 1)(x − 2)
Let's solve this problem step-by-step.
6+0.1x=0.15x+8
Step 1: Simplify both sides of the equation.
0.1x+6=0.15x+8
Step 2: Subtract 0.15x from both sides.
0.1x+6−0.15x=0.15x+8−0.15x
−0.05x+6=8
Step 3: Subtract 6 from both sides.
−0.05x+6−6=8−6
−0.05x=2
Step 4: Divide both sides by -0.05.
-0.05x/-0.05=2/-0.05
So, the answer for this problem is x=-40
Answer:
11.6 should be your answer!
Step-by-step explanation:
Im so sorry if its wrong!
Hope this helps!!
( > .< )
The GCF of 40 16 and 24 is 8
<h3>How to determine the GCF of 40 16 and 24?</h3>
The numbers are given as:
40 16 and 24
Start by listing out the factors of the numbers:
This is done as follows:
- The factors of 40 are: 1, 2, 4, 5, 8, 10, 20, 40
- The factors of 16 are: 1, 2, 4, 8, 16
- The factors of 24 are: 1, 2, 3, 4, 6, 8, 12, 24
Then the greatest common factor in the above list is 8.
Hence, the GCF of 40 16 and 24 is 8
Read more about GCF at:
brainly.com/question/219464
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Answer:
Test statistic Z= 0.13008 < 1.96 at 0.10 level of significance
null hypothesis is accepted
There is no difference proportion of positive tests among men is different from the proportion of positive tests among women
Step-by-step explanation:
<em>Step(I)</em>:-
Given surveyed two random samples of 390 men and 360 women who were tested
first sample proportion

second sample proportion

Step(ii):-
Null hypothesis : H₀ : There is no difference proportion of positive tests among men is different from the proportion of positive tests among women
Alternative Hypothesis:-
There is difference between proportion of positive tests among men is different from the proportion of positive tests among women

where

P = 0.920

Test statistic Z = 0.13008
Level of significance = 0.10
The critical value Z₀.₁₀ = 1.645
Test statistic Z=0.13008 < 1.645 at 0.1 level of significance
Null hypothesis is accepted
There is no difference proportion of positive tests among men is different from the proportion of positive tests among women