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Rzqust [24]
4 years ago
12

An integer N is to be selected at random from {1, 2, ... , (10)3 } in the sense that each integer has the same probability of be

ing selected. What is the probability that N will be divisible by 3? by 5? by 7? by 15? by 105? How would your answer change if (10)3 is replaced by (lO)k as k became larger and larger?
Mathematics
2 answers:
Feliz [49]4 years ago
8 0

Step-by-step explanation:

Step 1:

The variable N is to be selected at the random form which is  {1,2,.....,1000}

the total number of way that 1000 divisible by 3 = 1000/3 = 333.3

Here the favorable case = 333 ways  

The Exhaustive case = 1000 ways

Therefore, the probability that N can be divisible by 3 = 333/1000 = 0.333

Step 2:

The total number of way that 1000 divisible by 5 = 1000/5 = 200

Here the favorable case = 200 ways  

Therefore, the probability that N can be divisible by 5 = 200/1000 = 0.2

Step 4:

The total number of ways that 1000 divisible by 7 = 1000/7 = 142.85 = 143

Here the favorable case = 143 ways  

Step 5:

The total number of ways that 1000 divisible by 15 = 15/1000 = 66.6667 =67

Here the favorable case = 67 ways  

Therefore, the probability that N can be divisible by 15 = 67/1000 = 0.067

Step 7:

Similarly, the probability of N can be divided by 105 = 9.5238/1000 = 0.0095

Last step:

than, Similarly N is selected from {1,2,.....(10)^k} where the variable k is larger than the probability that N can be:

Divisible by 3 = 10^k/3/10^k = 0.33

Divisible by 5 = 1/5 = 0.2

Divisible by 7 = 1/7 = 0.413

Divisible by 15 = 1/15 = 0.0666

Divisible by 105 = 1/105 = 0.0095

Andrej [43]4 years ago
3 0

Answer:

Probability of N Divisible by 3 - 0.33

Probability of N Divisible by 5 - 0.2

Probability of N Divisible by 7 - 0.413

Probability of N Divisible by 15 - 0.066

Probability of N Divisible by 105 - 0.0095

Step-by-step explanation:

Given data:

Integer N {1,2,.....10^3}

Thus total number of ways by which 1000 is divisible by 3 i.e. 1000/3 = 333.3

Probability of N divisible by 3 {N%3 = 0 } = \frac{333.3}{1000} = 0.33

total number of ways by which 1000 is divisible by 5 i.e. 1000/5 = 200

Probability of N divisible by 5 {N%5 = 0 } = \frac{200}{1000} = 0.2

total number of ways by which 1000 is divisible by 7 i.e. 1000/7 = 142.857

Probability of N divisible by 7 {N%7 = 0 } = \frac{142.857}{1000} = 0.413

total number of ways by which 1000 is divisible by 15 i.e. 1000/15 = 66.667

Probability of N divisible by 15 {N%15 = 0 } = \frac{66.667}{1000} = 0.066

total number of ways by which 1000 is divisible by 105 i.e. 1000/105 = 9.52

Probability of N divisible by 105 {N%105 = 0 } = \frac{9.52}{1000} = 0.0095

similarly for N is selected from 1,2.....(10)^k where K is  large then the N value. Therefore effect of k will remain same as previous part.

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Phoenix [80]

Answer:

A 95% confidence interval for the mean number of chips in a bag of Chips Ahoy Cookies is [1187.96, 1288.44].

Step-by-step explanation:

We are given that statistics students at the Air Force Academy (no kidding) purchased some randomly selected bags of cookies and counted the chocolate chips.

Some of their data are given below; 1219, 1214, 1087, 1200, 1419, 1121, 1325, 1345, 1244, 1258, 1356, 1132, 1191, 1270, 1295, 1135.

Firstly, the pivotal quantity for finding the confidence interval for the population mean is given by;

                          P.Q.  =  \frac{\bar X-\mu}{\frac{s}{\sqrt{n} } }  ~ t_n_-_1

where, \bar X = sample mean number of chocolate chips = \frac{\sum X}{n} = 1238.2

            s = sample standard deviation = \sqrt{\frac{\sum (X-\bar X)^{2} }{n-1} }  = 94.3

            n = sample of car drivers = 16

            \mu = population mean number of chips in a bag

<em>Here for constructing a 95% confidence interval we have used a One-sample t-test statistics because we don't know about population standard deviation.</em>

<u>So, 95% confidence interval for the population mean, </u>\mu<u> is ;</u>

P(-2.131 < t_1_5 < 2.131) = 0.95  {As the critical value of t at 15 degrees of

                                             freedom are -2.131 & 2.131 with P = 2.5%}  

P(-2.131 < \frac{\bar X-\mu}{\frac{s}{\sqrt{n} } } < 2.131) = 0.95

P( -2.131 \times {\frac{s}{\sqrt{n} } } < {\bar X-\mu} < 2.131 \times {\frac{s}{\sqrt{n} } } ) = 0.95

P( \bar X-2.131 \times {\frac{s}{\sqrt{n} } } < \mu < \bar X+2.131 \times {\frac{s}{\sqrt{n} } } ) = 0.95

<u>95% confidence interval for</u> \mu = [ \bar X-2.131 \times {\frac{s}{\sqrt{n} } } , \bar X+2.131 \times {\frac{s}{\sqrt{n} } } ]

                                   = [ 1238.2-2.131 \times {\frac{94.3}{\sqrt{16} } } , 1238.2+2.131 \times {\frac{94.3}{\sqrt{16} } } ]

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Therefore, a 95% confidence interval for the mean number of chips in a bag of Chips Ahoy Cookies is [1187.96, 1288.44].

7 0
3 years ago
one half the cost of a dress decreased by $12 is the same as 2/5 the cost of a dress. What is the cost of the dress?
guajiro [1.7K]

Answer:

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Step-by-step explanation:

Let the cost of the dress be "c"

ONE HALF the cost DECREASED by 12, can be written as:

\frac{1}{2}c-12

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\frac{2}{5}c

Now, we equate both parts and solve for c to get cost of dress. Shown below:

\frac{1}{2}c-12=\frac{2}{5}c\\\frac{1}{2}c-\frac{2}{5}c=12\\\frac{5-4}{10}c=12\\\frac{1}{10}c=12\\c=\frac{12}{\frac{1}{10}}\\c=12*10\\c=120

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The ccost of the dress is $120

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Step-by-step explanation:

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