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dexar [7]
3 years ago
9

LMN is a right triangle. A= True B= False

Mathematics
1 answer:
Talja [164]3 years ago
5 0

Answer:

true

Step-by-step explanation:

it has a right angle!

me = big brain

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What is the volume of a sphere with an 18 inch diameter ?
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4 years ago
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How many possible outcomes are there when flipping a coin 9 times?
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3 years ago
An atlas contains a map of Ohio. The table shows data from the key on the map.
Rashid [163]

Answer:

The answer is below

Step-by-step explanation:

a) The graph is attached

b) The table shows a linear relationship between x and y.

A linear equation is in the form y = mx + b, where y is a dependent variable, x is an independent variable, m is the rate of change (slope) and b is the value of y when x = 0.

x represent the distance on map in mm and y represent the actual distance in mile. The table (x, y) has the points (10, 25) and (20, 50). The equation is given by:

y-y_1=\frac{y_2-y_1}{x_2-x_1} (x-x_1)\\\\y-25=\frac{50-25}{20-10} (x-10)\\\\y-25=2.5(x-10)\\\\y-25=2.5x-25\\\\y=2.5x

The slope m = 2.5. This means that for every 1 mm on the map, the actual distance increases by 2.5 miles.

c) y = 2.5x

put x = 48 mm

y = 2.5(48)

y = 120 miles

The actual distance between Toledo and Columbus is 120 miles

d) y = 2.5x

Put y = 225 miles

225 = 2.5x

x = 225/2.5

x = 90 mm

The distance on map between Cincinnati and Cleveland is about 90 mm.

8 0
3 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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