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Goshia [24]
3 years ago
14

2. The Miller family made mathematical statements out of their ages as follows. Tom is four less than tw

Mathematics
1 answer:
Taya2010 [7]3 years ago
6 0

Answer:the answer is B

Step-by-step explanation:

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She can't spend more than 5 minutes on each of the remaining 8 questions.

It's a 60-minute test in which she has spent 20 minutes answering 12 questions. That means that there are 40 minutes remaining (60-20) to answer the remaining 8 questions. That's 40 divided by 8 = 5.
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Two coins, A and B, each have a side for heads and a side for tails. When coin A is tossed, the probability it will land tails-s
BlackZzzverrR [31]

Answer:

Is the number of tosses for each coin enough for the sampling distribution of the difference in sample proportions PA-PB to be approximately normal?

b. No, 20 tosses for coin A is enough, but 20 tosses for coin B is not enough.

Step-by-step explanation:

a) Data and Calculations:

The probability of coin A landing tails-side up = 0.5

The proportion of times coin A lands tails-side up (PA) = 20 * 0.5 = 10

Therefore, the probability of coin A landing heads-side up = 0.5 (1 - 0.5)  

And the proportion of times that coin A lands heads-side up = 20 * 0.5 = 10.  

The proportion on either side is equally distributed.

This is why 20 tosses for coin A is enough, since the sample proportions PA is approximately normal, symmetric, and equally distributed.  There will be equal amounts of 10 tosses (0.5 *20) for either heads-side up or tails-side up.

For coin B, the probability of landing tails-side up = 0.8

The proportion of times coin B lands tails-side up (PB) = 20 * 0.8 = 16

Therefore, the probability of coin B landing heads-side up = 0.2 (1 - 0-.8)

The proportion on either side is not equally distributed, but skewed.

This is why 20 tosses for coin B is not enough, since the sample proportions PB is not approximately normal, symmetric, and equally distributed.  There will be 16 tosses landing tails-side up (0.8*20) and only 4 tosses landing heads-side up (0.2*20).

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