D. 192in^2
This would be a simple area problem with a triangle. REMEMBER THIS EQUATION: a=bh*1/2 (b for base and h for height, these are multiplied together then that answer is halved out.)
So we just need to plug in our values into the equation, so the equation would look like a= (16)*(24)*1/2. 16 times 24 would then give you 384, you could either divide by 2 or multiply by 0.5 to get the next answer, as long as your HALVING the answer.
So we have our bh value so now we can multiply by 1/2 which will give us 384*1/2 which leaves us with 192.
I have also attached a photo of doing a longer(ish) way than this, that also proves that this equation works. Either one will provide you an answer.
Here it is given that AB || CD
< EIA = <GJB
Now
∠EIA ≅ ∠IKC and ∠GJB is ≅ ∠ JLD (Corresponding angles)
∠EIA ≅ ∠GJB then ∠IKC ≅ ∠ JLD (Substitution Property of Congruency)
∠IKL + ∠IKC 180° and ∠DLH + ∠JLD =180° (Linear Pair Theorem)
So
m∠IKL + m∠IKC = 180° ....(1)
But ∠IKC ≅ ∠JLD
m∠IKC = m∠JLD (SUBTRACTION PROPERTY OF CONGRUENCY)
So we have
m∠IKL + m∠JLD = 180°
∠IKL and ∠JLD are supplementary angles.
But ∠DLH and ∠JLD are supplementary angles.
∠IKL ≅ ∠DLH (CONGRUENT SUPPLEMENTS THEOREM)
The slope is -3x i think
just a tip there’s this website (i think there’s an app too?). allied khan academy it’s basically for school and there’s lots of videos of what you’re doing
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