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Lena [83]
1 year ago
12

The number of typos made by a student follows Poisson distribution with the rate of 1.5 typos per page. Assume that the numbers

of typos on different pages are independent. (a) Find the probability that there are at most 2 typos on a page. (b) Find the probability that there are exactly 10 typos in a 5-page paper. (c) Find the probability that there are exactly 2 typos on each page in a 5-page paper. (d) Find the probability that there is at least one page with no typos in a 5-page paper. (e) Find the probability that there are exactly two pages with no typos in a 5-page paper.
Mathematics
1 answer:
crimeas [40]1 year ago
3 0

Answer:

a) 0.8088 = 80.88% probability that there are at most 2 typos on a page.

b) 0.0858 = 8.58% probability that there are exactly 10 typos in a 5-page paper.

c) 0.001 = 0.1% probability that there are exactly 2 typos on each page in a 5-page paper.

d) 0.717 = 71.7% probability that there is at least one page with no typos in a 5-page paper.

e) 0.2334 = 23.34% probability that there are exactly two pages with no typos in a 5-page paper.

Step-by-step explanation:

Poisson distribution:

In a Poisson distribution, the probability that X represents the number of successes of a random variable is given by the following formula:

P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!}

In which

x is the number of sucesses

e = 2.71828 is the Euler number

\mu is the mean in the given interval.

Binomial distribution:

The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

In which C_{n,x} is the number of different combinations of x objects from a set of n elements, given by the following formula.

C_{n,x} = \frac{n!}{x!(n-x)!}

And p is the probability of X happening.

The number of typos made by a student follows Poisson distribution with the rate of 1.5 typos per page.

This means that \mu = 1.5n, in which n is the number of pages.

(a) Find the probability that there are at most 2 typos on a page.

One page, which means that \mu = 1.5

This is

P(X \leq 2) = P(X = 0) + P(X = 1) + P(X = 2)

In which

P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!}

P(X = 0) = \frac{e^{-1.5}*(1.5)^{0}}{(0)!} = 0.2231

P(X = 1) = \frac{e^{-1.5}*(1.5)^{1}}{(1)!} = 0.3347

P(X = 2) = \frac{e^{-1.5}*(1.5)^{2}}{(2)!} = 0.2510

P(X \leq 2) = P(X = 0) + P(X = 1) + P(X = 2) = 0.2231 + 0.3347 + 0.2510 = 0.8088

0.8088 = 80.88% probability that there are at most 2 typos on a page.

(b) Find the probability that there are exactly 10 typos in a 5-page paper.

5 pages, which means that n = 5, \mu = 5(1.5) = 7.5.

This is P(X = 10). So

P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!}

P(X = 10) = \frac{e^{-7.5}*(7.5)^{10}}{(10)!} = 0.0858

0.0858 = 8.58% probability that there are exactly 10 typos in a 5-page paper.

(c) Find the probability that there are exactly 2 typos on each page in a 5-page paper.

Two typos on a page: 0.2510 probability.

Two typos on each of the 5 pages: (0.251)^5 = 0.001

0.001 = 0.1% probability that there are exactly 2 typos on each page in a 5-page paper.

(d) Find the probability that there is at least one page with no typos in a 5-page paper.

0.2231 probability that a page has no typo, so 1 - 0.2231 = 0.7769 probability that there is at least one typo in a page.

(0.7769)^5 = 0.283 probability that every page has at least one typo.

1 - 0.283 = 0.717 probability that there is at least one page with no typos in a 5-page paper.

(e) Find the probability that there are exactly two pages with no typos in a 5-page paper.

Here, we use the binomial distribution.

0.2231 probability that a page has no typo, so p = 0.02231

5 pages, so n = 5

We want P(X = 2). So

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

P(X = 2) = C_{5,2}.(0.2231)^{2}.(0.7769)^{3} = 0.2334

0.2334 = 23.34% probability that there are exactly two pages with no typos in a 5-page paper.

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Answer:

1)

Null hypothesis            H₀ : μ = 25,809

Alternative hypothesis H₁ : μ < 25,809

2) Test Statistic = -1.44

3) Conclusion:

The result is significant, there is sufficient evidence to support the bride’s hope at the 0.10 level of significance.

Step-by-step explanation:

Given the data in the question;

Sample mean x" = 24,638

sample size n = 46

standard deviation σ = 5531

level of significance ∝ = 0.10

NULL and ALTERNATIVE HYPOTHESIS

Null hypothesis            H₀ : μ = 25,809

Alternative hypothesis H₁ : μ < 25,809

TEST STATISTICS

Z = (x"-μ) / σ√n

we substitute

Z = (24,638 - 25,809) / (5531/√46)

Z = -1171 / 815.5

Z = -1.44

Test Statistic = -1.44

Now, from normal z-table;

P-value = P( Z < -1.44 ) = 0.0749

P-value = 0.0749

Since P-value ( 0.0749 ) is less than level of significance ( 0.10 ), we reject H₀.

Conclusion:

The result is significant, there is sufficient evidence to support the bride’s hope at the 0.10 level of significance.

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2 years ago
Oishi and Schimmack (2010) report that people who move from home to home frequently as children tend to have lower than average
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Answer:

The well-being for frequent movers is significantly different from well-being in the general population. ( Alternate Hypothesis accepted )

cohen's d = -0.91 , ( Large Effect )

Step-by-step explanation:

Given:-

- A sample of size n = 12

- The population mean u_p = 40

- The sample was taken as:

                     38, 37, 41, 35, 42, 40, 33, 33, 36, 38, 32, 39

Find:-

On the basis of this sample, is well-being for frequent movers significantly different from well-being in the general population? Use a two-tailed test with α = 0.05.

Solution:-

- State the hypothesis for sample mean u_s is same as population mean u_p.

                    Null Hypothesis: u_s = 40

                    Alternate Hypothesis: u_s ≠ 40

- The rejection criteria for the Null hypothesis can be modeled by T-value ( n < 30 ) with significance level α = 0.05.

                    DOF = n - 1 = 12 - 1 = 11

                    Significance level α = 0.05

                    t_α/2 = t_0.025 = +/- 2.201

- For the statistic value we have to compute sample mean u_s given by:

             u_s = Σ xi / n

             u_s = (38 + 37 + 41 + 35 + 42 + 40 + 33 + 33 + 36 + 38 + 32 + 39) / 12

             u_s = 37

- For the statistic value we need population standard deviation S_p given by:

            S_p = S_s / √n

Where, S_s : Sample standard deviation.

            S_s^2 = Σ (xi - u_s)^2 / (n-1)

            =[ 2*(38-37)^2 +  (37-37)^2 + (41-37)^2 + (35-37)^2 + (42-37)^2 + (40-37)^2 + 2*(33-37)^2 + (36-37)^2 + (32-37)^2 + (39-37)^2 ] / ( 11 )

            S_s^2 = [ 2 + 0 + 16 + 4 + 25 + 9 + 32 + 1 + 25 + 4 ] / 11

            S_s^2 = 10.73

            S_s = 3.28

The population standard deviation ( S_p ) is:

            S_p = 3.28 / √12

            S_p = 0.95

- The T-statistics value is computed as follows:

            t = ( u_s - u_p ) / S_p

            t = ( 37 - 40 ) / 0.95 = -3.16

- Compare the T-statistics (t) with rejection criteria (t_α/2).

            -3.16 < -2.201

            t < t_α/2 ...... Reject Null Hypothesis.

- The well-being for frequent movers is significantly different from well-being in the general population. ( Alternate Hypothesis accepted )

- The cohen's d is calculated as follows:

         cohen's d = ( u_s - u_p ) / S_s

         cohen's d = ( 37 - 40 ) / 3.28 = -0.91 ,     ( Large Effect )    

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Answer:

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sin(\theta)=-\frac{\sqrt{2}}{2}

tan(\theta)=-1

Step-by-step explanation:

we know that

tan(\theta)=\frac{sin(\theta)}{cos(\theta)}

sin^{2}(\theta)+cos^{2}(\theta)=1

In this problem we have

cos(\theta)=\frac{\sqrt{2}}{2}

\frac{3\pi}{2}

so

The angle \theta belong to the third or fourth quadrant

The value of sin(\theta) is negative

Step 1

Find the value of  sin(\theta)

Remember

sin^{2}(\theta)+cos^{2}(\theta)=1

we have

cos(\theta)=\frac{\sqrt{2}}{2}

substitute

sin^{2}(\theta)+(\frac{\sqrt{2}}{2})^{2}=1

sin^{2}(\theta)=1-\frac{1}{2}

sin^{2}(\theta)=\frac{1}{2}

sin(\theta)=-\frac{\sqrt{2}}{2} ------> remember that the value is negative

Step 2

Find the value of tan(\theta)

tan(\theta)=\frac{sin(\theta)}{cos(\theta)}

we have

sin(\theta)=-\frac{\sqrt{2}}{2}

cos(\theta)=\frac{\sqrt{2}}{2}

substitute

tan(\theta)=\frac{-\frac{\sqrt{2}}{2}}{\frac{\sqrt{2}}{2}}

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