The theorem that justifies why triangles ABC and DEF are congruent is: HL.
<h3>What is the Hypotenuse-Leg Congruence Theorem (HL)?</h3>
The hypotenuse-leg congruence theorem (HL) states that if two triangles that are right triangles have a pair of congruent hypotenuse and a pair of corresponding congruent legs, then both right triangles are proven to be congruent to each other. This means both right triangles are have the same shape and size.
Given that:
angle ABC = angle DEF = 90° (congruent right angles, this means both triangles are right triangles)
AC = FD (a pair of congruent hypotenuse)
AB = DE (a pair of congruent legs)
Thus, we can conclude that since triangle ABC and triangle DEF have a pair of congruent hypotenuses and a pair of congruent legs, therefore, the two right triangles, triangle ABC and triangle DEF are congruent to each other by the HL congruent theorem.
Thus, the theorem that justifies why both triangles are congruent is: HL.
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Answer:
200-50-40=B
B =110 blue pieces
Step-by-step explanation:
Example
if ab=6
and a=3
b=2
a. 6 must be factor of 3 or 2 FALSE
b. 3 must be a factor of 3 OR 2 TRUE
c. 3 must be a factor of 3 AND 2 FALSE
B is true
Binomial conditions<span>fixed number of trials
each trial must be either a success or a fail
trails must be independent
the value of P must remain constant</span>Binomial E(X)npBinomial Var(X)np(1-p)Poisson conditions<span>events must be independent
events must occur singly in space or time
event must occur at a constant rate</span>poisson E(X)£Var(X)£binomial to normal<span>n is large
p is close to 0.5
N(np,np(1-p)
np>10</span>binomial to poisson<span>n is large
p is small
Po(np)
np<10</span>poisson to normal<span>n is large
N(£,£)</span>populationa collection of itemscensusinformation obtained from every member of a populationsamplea selection of indvidual members from a populationpopulation parameterany characteristic of a population which is measurablefinite populationa population in whihc every individual member can be given a numberinfinite populationa population which is impossible to give a number to every individualadvantage censusevery single member of a population is used, unbiased, gives an accurate answerdisadvantage censustime consuming, costly, difficult to ensure that the whole population is surveyeddisadvantage sample<span>natural variation
bias</span>advantage sample<span>sample is representative
cheaper
data more readily avalible</span>poisson<span>events occur randomly
singly in space or time
independently of each other
constant rate</span>binomial<span>fixed number of trials
each trail either a success or failure
trails independent
probability of success constant</span>significance levelprobability of incorrectly rejecting the null hypothesisstatisticrandom variable quantity calculated soley from observations in a sample does not involve any unknown parameters numerical property of a samplesampling distributionall possible values of a test statistic and their probabilitiessampling framea list of all the sampling units within a populationsampling unitsthe individual units of a populationsample surveyan investigation using a samplerandom samplingevery possible sample of size n has an equal chance of being selectedhypothesisa statement made about the value of a population parameternull hypothesishypothesis that is assumed to be correcttest statistica form of a statistic in which the evidence from a sample in a hypothesis test is summarisedcritical valuesthe values on the boundaries
Answer:
c
Step-by-step explanation:
