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mr_godi [17]
3 years ago
6

Need answers now. Not good with geometry or Algebra.​

Mathematics
1 answer:
ICE Princess25 [194]3 years ago
3 0

Answer:

x = 4.98

Step-by-step explanation:

Since this is a right triangle, we can use trig functions

sin theta = opp / hyp

sin 50 = x/6.5

6.5 sin 50 =x

x=4.97928

x = 4.98

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Answer:

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Scot wants to buy a scooter that cost $129 this is$24 more than 3 times what He saved last month how much he did save last month
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Total $129

129 - 24 = 105

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Scot saves $35 last month
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3 years ago
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A fabric manufacturer believes that the proportion of orders for raw material arriving late isp= 0.6. If a random sample of 10 o
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Answer:

a) the probability of committing a type I error if the true proportion is p = 0.6 is 0.0548

b)

- the probability of committing a type II error for the alternative hypotheses p = 0.3 is 0.3504

- the probability of committing a type II error for the alternative hypotheses p = 0.4 is 0.6177

- the probability of committing a type II error for the alternative hypotheses p = 0.5 is 0.8281

Step-by-step explanation:

Given the data in the question;

proportion p = 0.6

sample size n = 10

binomial distribution

let x rep number of orders for raw materials arriving late in the sample.

(a) probability of committing a type I error if the true proportion is  p = 0.6;

∝ = P( type I error )

= P( reject null hypothesis when p = 0.6 )

= ³∑_{x=0 b( x, n, p )

= ³∑_{x=0 b( x, 10, 0.6 )

= ³∑_{x=0 \left[\begin{array}{ccc}10\\x\\\end{array}\right](0.6)^x( 1 - 0.6 )^{10-x

∝ = 0.0548

Therefore, the probability of committing a type I error if the true proportion is p = 0.6 is 0.0548

b)

the probability of committing a type II error for the alternative hypotheses p = 0.3

β = P( type II error )

= P( accept the null hypothesis when p = 0.3 )

= ¹⁰∑_{x=4 b( x, n, p )

= ¹⁰∑_{x=4 b( x, 10, 0.3 )

= ¹⁰∑_{x=4 \left[\begin{array}{ccc}10\\x\\\end{array}\right](0.3)^x( 1 - 0.3 )^{10-x

= 1 - ³∑_{x=0 \left[\begin{array}{ccc}10\\x\\\end{array}\right](0.3)^x( 1 - 0.3 )^{10-x

= 1 - 0.6496

= 0.3504

Therefore, the probability of committing a type II error for the alternative hypotheses p = 0.3 is 0.3504

the probability of committing a type II error for the alternative hypotheses p = 0.4

β = P( type II error )

= P( accept the null hypothesis when p = 0.4 )

= ¹⁰∑_{x=4 b( x, n, p )

= ¹⁰∑_{x=4 b( x, 10, 0.4 )

= ¹⁰∑_{x=4 \left[\begin{array}{ccc}10\\x\\\end{array}\right](0.4)^x( 1 - 0.4 )^{10-x

= 1 - ³∑_{x=0 \left[\begin{array}{ccc}10\\x\\\end{array}\right](0.4)^x( 1 - 0.4 )^{10-x

= 1 - 0.3823

= 0.6177

Therefore, the probability of committing a type II error for the alternative hypotheses p = 0.4 is 0.6177

the probability of committing a type II error for the alternative hypotheses p = 0.5

β = P( type II error )

= P( accept the null hypothesis when p = 0.5 )

= ¹⁰∑_{x=4 b( x, n, p )

= ¹⁰∑_{x=4 b( x, 10, 0.5 )

= ¹⁰∑_{x=4 \left[\begin{array}{ccc}10\\x\\\end{array}\right](0.5)^x( 1 - 0.5 )^{10-x

= 1 - ³∑_{x=0 \left[\begin{array}{ccc}10\\x\\\end{array}\right](0.5)^x( 1 - 0.5 )^{10-x

= 1 - 0.1719

= 0.8281

Therefore, the probability of committing a type II error for the alternative hypotheses p = 0.5 is 0.8281

3 0
3 years ago
PLEASE HELP WITH GEOMETRY QUESTION!! FIND H
Yakvenalex [24]

Answer:

we have

when

base=8cm

height=11cm

area of parallelogram is :base×height

=8*11=88cm³

Now for

base=15cm

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the area of parallelogram=88cm²

base ×height=88cm²

15*h=88

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When randomly selecting an​ adult, A denotes the event of selecting someone with blue eyes. What do Upper P (Upper A )P(A) and U
bezimeni [28]

Answer:

P(A): It is the probability of selecting someone with blue eyes.  

P(\bar{A}): It is the probability of selecting someone who does not have blue eyes

Step-by-step explanation:

We are given the following in the question:

A: event of selecting someone with blue eyes.

Probability:

  • The probability of an event tells the chances of happening of that event.
  • It is mathematically defined as:

\text{Probability} = \displaystyle\frac{\text{Number of favourable outcomes}}{\text{Total number of outcomes}}

Complement of an event:

  • It is the event that consist of all outcomes not happening in A.
  • It is represented by \bar{A}
  • P(A) + P(\bar{A}) = 1

We have to explain the representation:

a) P(A): It is the probability of selecting someone with blue eyes.

It gives us the chances of someone having blue eyes.

b) P(\bar{A}): It is the probability of selecting someone who does not have blue eyes

It is the chances of selecting someone who does not have blue eyes.

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