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sesenic [268]
4 years ago
8

The net weight in pounds of a packaged chemical herbicide is uniform for 49.62 < x < 50.04 pounds.

Mathematics
1 answer:
k0ka [10]4 years ago
6 0

Answer:

a) E(X)=\frac{50.64+49.62}{2}=50.13 pounds

b) Var(X)= \frac{(b-a)^2}{12} =\frac{(50.04-49.62)^2}{12}=0.0147

c) P(X

But we see that the distribution is defined ust between 49.62 and 50.04

And in order to find this we can use the CDF (Cumulative distribution function) given by:

F(X) =\frac{x-a}{b-a}

And if we replace we got:

P(X

And makes sense since all the values are between 49.62 and 50.04

Step-by-step explanation:

For this case we define the random variable X ="net weigth in pounds of a packaged chemical herbicide" and the distribution for X is given by:

X \sim U(a= 49.62, b=50.04)

Part a

For the uniform distribution the expected value is given by E(X) =\frac{a+b}{2} where X is the random variable, and a,b represent the limits for the distribution. If we apply this for our case we got:

E(X)=\frac{50.64+49.62}{2}=50.13 pounds

Part b

The variance for an uniform distribution is given by:

Var(X)= \frac{(b-a)^2}{12}

And if we replace we got:

Var(X)= \frac{(b-a)^2}{12} =\frac{(50.04-49.62)^2}{12}=0.0147

Part c

For this case we want to find this probability:

P(X

But we see that the distribution is defined ust between 49.62 and 50.04

And in order to find this we can use the CDF (Cumulative distribution function) given by:

F(X) =\frac{x-a}{b-a}

And if we replace we got:

P(X

And makes sense since all the values are between 49.62 and 50.04

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The random variable x is the number of occurrences of an event over an interval of ten minutes. It can be assumed that the proba
givi [52]

The options given don't correspond to the values in the question. The options are from another question where mean is 5.3 and the probability being looked for is for exactly 3 occurrences and 5 occurrences

Answer:

A) 0.6511

B) Poisson distribution

Step-by-step explanation:

We are given;

Mean: μ = 5.4 minutes

Now, we want to find the probability that there are more than 5 occurrences in ten minutes.

This will be written as;

P(x > 5) = 1 - P(x < 5)

P(x < 5) = P(x = 4) + P(x = 3) + P(x = 2) + P(x = 1) + P(x = 0)

We will use Poisson distribution for this. The formula is;

P(x) = [(e^(-μ)) × μ^(x)]/x!

P(0) = [(e^(-5.4)) × 5.4^(0)]/0! = 0.004517

P(1) = [(e^(-5.4)) × 5.4^(1)]/1! = 0.02439

P(2) = [(e^(-5.4)) × 5.4^(2)]/2! = 0.06585

P(3) = [(e^(-5.4)) × 5.4^(3)]/3! = 0.11853

P(4) = [(e^(-5.4)) × 5.4^(4)]/4! = 0.16

Thus;

P(x < 5) = 0.16 + 0.11853 + 0.06585 + 0.004517 = 0.3489

Thus;

P(x > 5) = 1 - P(x < 5) = 1 - 0.3489 = 0.6511

B) like seen from solution A above, we used Poisson distribution formula.

Thus, random variable x satisfies Poisson distribution

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Answer:

p_v= 0.01

Since the significance level is 0.05 we see that pv so we have enough evidence to reject the null hypothesis. And the best conclusion for this case would be:

b. at least some, but not all, of the gestation periods across all four species are the same

Because is only to identify if AT LEAST one mean is different, NOT to conclude that the all the means are different.

Step-by-step explanation:

Previous concepts

Analysis of variance (ANOVA) "is used to analyze the differences among group means in a sample".  

The sum of squares "is the sum of the square of variation, where variation is defined as the spread between each individual value and the grand mean"  

Solution to the problem

The hypothesis for this case are:

Null hypothesis: \mu_{A}=\mu_{B}=\mu_{C}= \mu_D

Alternative hypothesis: Not all the means are equal \mu_{i}\neq \mu_{j}, i,j=A,B,C,D

In order to find the mean square between treatments (MSTR), we need to find first the sum of squares and the degrees of freedom.

If we assume that we have p=4 groups and on each group from j=1,\dots,p we have n_j individuals on each group we can define the following formulas of variation:  

SS_{total}=\sum_{j=1}^p \sum_{i=1}^{n_j} (x_{ij}-\bar x)^2  

SS_{between}=SS_{model}=\sum_{j=1}^p n_j (\bar x_{j}-\bar x)^2  

SS_{within}=SS_{error}=\sum_{j=1}^p \sum_{i=1}^{n_j} (x_{ij}-\bar x_j)^2  

And we have this property  

SST=SS_{between}+SS_{within}  

And in order to test this hypothesis we need to ue an F statistic and for this case the p value calculated is

p_v= 0.01

Since the significance level is 0.05 we see that pv so we have enough evidence to reject the null hypothesis. And the best conclusion for this case would be:

b. at least some, but not all, of the gestation periods across all four species are the same

Because is only to identify if AT LEAST one mean is different NOT to conclude that the all the means are different.

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