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3 years ago

98 Points! Answer Quick!

Mathematics

2 answers:

timama [110]3 years ago

7 0

Reason:

2. SD ⊥ HT. ∴ ∠SDH = ∠SDT =90°

3. Given (It is given in the question)

5. RHS congruence

(Here, the right angle, hypotenuse and one side of ΔSHD is congruent to that of ΔSTD).

Statement:

4. Line segment SD = SD

(Reflexive property is used to prove congruence of triangles. This property is used when an angle or line segment is congruent to itself.)

Lina20 [59]3 years ago

6 0

Answer:

2. SD ⊥ HT. ∴ ∠SH = ∠ST =90° 3.

Step-by-step explanation:

Two right triangles are congruent if the hypotenuse and one side of one triangle are respectively equal to the hypotenuse and the corresponding side of the other triangle.

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3 years ago

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3 years ago

Consider the random experiment of tossing 3 fair coins and observing how many of them come to rest with the heads side of the co

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Answer:

b. S = AUB

Step-by-step explanation:

Since the coins are tossed 3 times and each coin has head, H and tail, T(2 sides), the sample space is S = 2 × 2 × 2 = 2³ = 8

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Since S denote the sample space

S = {HTT, HHT, HHH, THH, TTH, HTH,THT, TTT}

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Also B denote the event that none of the coins comes to rest with its heads side upwards, that is no heads. The possible outcome is TTT

So, B = {TTT}

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S = {HTT, HHT, HHH, THH, TTH, HTH,THT, TTT}

So, A ∪ B = {HTT, HHT, HHH, THH, TTH, HTH,THT} ∪ {TTT} = {HTT, HHT, HHH, THH, TTH, HTH,THT, TTT} = S

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So, S = A ∪ B does not denote an abuse of notation.

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3 years ago

The mean annual income for adult women in one city is $28,520 and the standard deviation of the incomes is $5600. The distributi

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Answer:

$E(\bar{x}) = 28520$

Standard error of mean = 689

Step-by-step explanation:

We are given the following information in the question:

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Standard Deviation, σ = $5600

Mean of sampling distribution =

$E(\bar{x}) = \mu = 28520$

As per Central Limit Theorem, if the sample size is large enough, then the sampling distribution of the sample means follow approximately a normal distribution.

Sample size, n = 66

Since the sample size is large, we can use normal distribution for approximation.

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3 years ago