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svlad2 [7]
2 years ago
11

In the United States, 75 percent of adults wear glasses or contact lenses. A random sample of 10 adults in the United States wil

l be selected.
What is closest to the probability that fewer than 8 of the selected adults wear glasses or contact lenses?
Mathematics
1 answer:
V125BC [204]2 years ago
4 0

Answer:

0.4745 is the probability that fewer than 8 of the selected adults wear glasses or contact lenses.

Step-by-step explanation:

We are given the following information:

We treat adult adults wear glasses or contact lenses as a success.

P(Adults wear glasses or contact lenses) = 75% = 0.75

Then the number of adults follows a binomial distribution, where

P(X=x) = \binom{n}{x}.p^x.(1-p)^{n-x}

where n is the total number of observations, x is the number of success, p is the probability of success.

Now, we are given n = 10

We have to evaluate:

P(fewer than 8 of the selected adults wear glasses or contact lenses)

P(x < 8)\\=1 - P(x = 8) - P(x = 9) - P(x = 10)\\=1 - \binom{10}{8}(0.75)^8(1-0.75)^2 - \binom{10}{9}(0.75)^9(1-0.75)^1- \binom{10}{10}(0.75)^10(1-0.75)^0\\=1 - 0.2815-0.1877-0.0563\\= 0.4745

0.4745 is the probability that fewer than 8 of the selected adults wear glasses or contact lenses.

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a

The Null hypothesis represented as

     H_0: \mu_1 -  \mu_2  = 0

   

The Alternative hypothesis represented as

     H_a: \mu_1 -  \mu_2  <  0

b

p-value =  P(Z <  -3.37  )  = 0.000376

c

There is insufficient evidence to conclude that graduate students score higher, on average, on the HPI than undergraduate students

Step-by-step explanation:

From the question we are told that

   The population size is  n= 650

    The  sample size for graduates is  n_1 =  300

     The sample  mean for graduates is \= x _1 =  148

      The sample  standard deviation for graduates is \sigma_1  =  16

    The  sample size for under-graduates is n _2 = 350

         The sample  mean for under-graduates is \= x _2 =  153

         The sample  standard deviation for graduates is \sigma_2  =  21

The Null hypothesis represented as

     H_0: \mu_1 -  \mu_2  = 0

   

The Alternative hypothesis represented as

     H_a: \mu_1 -  \mu_2  <  0

Where \mu_1 \ and \  \mu_2 are the population mean

  Now the test statistic is mathematically represented as

          t =  \frac{(\= x_1 - \= x_2 ) }{ \sqrt{ \frac{ (n_1 - 1 )\sigma_1 ^2 + (n_2 - 1)\sigma_2^2}{n_1 +n_2 -2} }  * \sqrt{ \frac{1}{n_1}  + \frac{1}{n_2} } }

substituting values

       t =  \frac{(148 - 153 ) }{ \sqrt{ \frac{ (300- 1 )16 ^2 + (350 - 1) 21^2}{300 +350 -2} }  * \sqrt{ \frac{1}{300}  + \frac{1}{350} } }

      t = -3.37

The p-values is mathematically evaluated as

     p-value =  P(Z <  -3.37  )  = 0.000376

The above answer is gotten using a p-value calculator  at (0.05) level of significance

     Looking the p-value we see that it is less than the level of significance (0.05)  so Null hypothesis is rejected

Hence there is insufficient evidence to conclude that graduate students score higher, on average, on the HPI than undergraduate students

   

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2 years ago
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