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Harrizon [31]
3 years ago
10

1- A is a ratio that compares a number to 100. 2. A is an equation that shows that two ratios are equivalent. 3. In a one ratio

compares a part to a whole. 4. A number that can be written as a fraction is a H i . . p 5. The is the least common multiple of the denominators of two or more fractions.

Mathematics
1 answer:
Katarina [22]3 years ago
3 0
1. Percentage

2. Proportion

3. Fraction

4. Rational number (you are correct)

5. LCD (Least common multiple)
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Mind my hand writing but I’m not sure what sign to put the “-“ or the “+” ?
Ierofanga [76]

hello!

so the answer that you put there is actually wrong and i'll tell you why and how to do it

so since you are adding the two:

-8x + 9x = x (so you got this part right)

-12 + 4 = -8 (this is where you got it wrong, -12 added 4 goes up in value to -8)

so the final answer is x - 8

i hope this helped and have a nice day!

4 0
3 years ago
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ANSWER THIS CORRECTLY FOR BRAINLIEST (ALGEBRA)
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Answer:

33.49 cubic inches

Step-by-step explanation:

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A circular tablecloth covers a table with a diameter of 5 feet.The tablecloth hangs down an extra 6 inches al around.How much tr
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Step-by-step explanation:

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2 years ago
A new screening test for Lyme disease is developed for use in the general population. The sensitivity and specificity of the new
faltersainse [42]

Answer:

The predictive value of a positive test is 18.2%.

Step-by-step explanation:

The population screened is 300.

The true prevalence value of the Lyme disease among clinic attendees is 10\% \Rightarrow 0.10.10% = 0.10.

The proportion that sensitivity is 60\% \Rightarrow 0.6060% = 0.60

The proportion of the specificity is 70\% \Rightarrow 0.70.70% = 0.70

Step 2 of 2

We have to calculate the probability value of the predictive value of positive test.

\begin{array}{c}\\\left( \begin{array}{l}\\{\rm{Positive Predictive }}\\\\{\rm{value}}\left( {PPV} \right)\\\end{array} \right) = \frac{{{\rm{Prevalence}} \times {\rm{Sensitivity}}}}{{\left( {{\rm{Prevalence}} \times {\rm{Sensitivity}}} \right) + \left( {{\rm{1 - Prevalence}} \times 1 - {\rm{Specificity}}} \right)}}\\\\ = \frac{{0.1 \times 0.60}}{{\left( {0.1 \times 0.60} \right) + \left( {1 - 0.1 \times 1 - 0.70} \right)}}\\\\ = \frac{{0.06}}{{0.33}}\\\\ = 0.181818\\\\ = 0.182{\rm{ }}\left( {{\rm{Round to 3 decimal place}}} \right)\\\end{array}  

(Positive Predictive  value, PPV) =

(Prevalence×Sensitivity)/Prevalence×Sensitivity +(1−Prevalence×1−Specificity)  

=   (0.1×0.60)/0.1×0.60  + (1−0.1×1−0.70) ​  

=    0.06 /0.33    

=   0.181818

(Positive Predictive  value, PPV) = 0.182 (3decimals)    

We have to convert the PPV into percentage,

\begin{array}{c}\\PPV = 0.182 \times 100\\\\ = 18.2\% \\\end{array}  

PPV=0.182×100

= 18.2% ​  

Therefore, the predictive positive value is 18.2%.

7 0
3 years ago
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