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Sergeu [11.5K]
3 years ago
12

in an election between two candidates one got 55% of the total valid votes 20% votes were invalid if the total number of votes w

ere 7500 what was the number of the violent vote that the other candidate got​
Mathematics
1 answer:
timurjin [86]3 years ago
4 0

Answer:

25%- 1875 Votes

<em>7500 x 0.55 = 4125  (</em><em>first candite valid votes</em><em>)</em>

<em>7500 x 0.20 = 1500 (</em><em>invalid</em><em>)</em>

<em>first candite valid votes</em><em> </em><em>(</em><em>55</em><em>) + invalid votes (</em><em>20</em><em>) = 75% of total votes </em>

<em>first candite valid votes</em><em> </em><em>(</em><em>4125</em><em>) + invalid votes (</em><em>1500 </em><em>) = 5625 of total votes </em>

<em />

<em>100 (</em><em>total</em><em> </em><em>percent of votes</em><em>) - 75 (</em><em>total percent of votes</em><em>) = 25% Votes Left</em>

<em>7500 (</em><em>total</em><em> </em><em>number of votes</em><em>) - 5625 (</em><em>total number of votes</em><em>) = 1875 Votes Left</em>

<em>7500 x 0.25 = 1875 (</em><em>valid votes for the other candite</em><em>)</em>

<em>          </em>

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See the explanation for the answer.

Step-by-step explanation:

Given function:

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                                                                                  (0.0000018522752) (x-81)³

p_{3} (x)  =  0.0092592593 x - 0.000042866941 (x - 81)² + 0.00000030871254

                                                                                                       (x-81)³ + 2.25

Hence approximation at given quantity i.e.

x = 94

Putting x = 94

p_{3} (94)  =  0.0092592593 (94) - 0.000042866941 (94 - 81)² +          

                                                                 0.00000030871254 (94-81)³ + 2.25

         = 0.87037 03742 - 0.000042866941 (13)² + 0.00000030871254(13)³ +    

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                                                                      0.00000030871254(2197) + 2.25

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Compute the absolute error in the approximation assuming the exact value is given by a calculator.

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If you round off the values then you get error as:

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If you round off the values up to 4 decimal places then you get error as:

|3.1138 - 3.1137| = 0.0001

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A type I error happens when a true null hypothesis is rejected.

A type II error happens when a false null hypothesis is failed to be rejected.

In this case, where the alternative hypothesis is that "the percentage of adults who retire at age 65 is greater than 62%", the null hypothesis will state that this percentage is not significantly greater than 62%.

A type I error would happen when the conclusion is that the percentage is greater than 62%, when in fact it is not.

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