if you flip a coin 10 times, what is the best prediction possible for the number of times it will land on heads?

Mathematics

2 answers:

lawyer [7]3 years ago

7 0

I think that it is a 50 / 50 chance it will land on head or tails.

( hoped this helped) :)

SVETLANKA909090 [29]3 years ago

4 0

Proabably. 5 because if there is 2 sides on a coin then you should divide 10÷2 which is 5.

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Two cards are chosen from a standard deck of 52 playing cards without replacement. What is the probability that the first card i

Rashid [163]

For the first draw, the probability of an ace is ( 4 / 52 ).

Now there are only 51 cards left in the deck.

For the second draw, the probability of a king is ( 4 / 51 ).

The probability of both events is

(4/52) (4/41) = (16/2,652)

Divide top and bottom by 4:

(16/2,652) = <em>4/663</em> . That's <em>choice-C </em>.

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A sample of 13 sheets of cardstock is randomly selected and the following thicknesses are measured in millimeters. Give a point

valina [46]

<h3>Answer: 0.061</h3>

===============================================

Explanation:

Add up the values to get

1.96+1.81+1.97+1.83+1.87+1.84+1.85+1.94+1.96+1.81+1.86+1.95+1.89= 24.54

Then divide over 13 (the number of values) to get 24.54/13 = 1.8876923 which is approximate.

So the mean is approximately 1.8876923

---------------------

Now make a spreadsheet as shown below

We have the first column as the x values, which are the original numbers your teacher provided. The second column is of the form (x-M)^2, where M is the mean we computed earlier. We subtract off the mean and square the result.

After we compute that column of (x-M)^2 values, we add them up to get what is shown in the highlighted yellow cell at the bottom of the column.

That sum is approximately 0.04403076924

Next, we divide that over n-1 = 13-1 = 12

0.04403076924 /12 = 0.00366923077

That is the sample variance. Apply the square root to this to get the sample standard deviation. This is the point estimate of the population standard deviation. As the name implies, it works for samples that estimate population parameters.

sqrt(0.00366923077) = 0.06057417576822

This rounds to 0.061 which is the final answer.