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makvit [3.9K]
2 years ago
7

A store manager is looking at past jewelry sales to determine what sizes of rings to keep in stock. The list shows the ring size

s purchased by the last ten jewelry customers. 9, 7, 6.5, 7.5, 7, 8, 5, 6, 7.5, 8 What is the variance of the data? Round to the nearest hundredths.
0.40
0.72
1.15
2.14
Mathematics
2 answers:
Rom4ik [11]2 years ago
4 0
Mean: ( 9 + 7 + 6.5 + 7.5 + 7 + 8 + 5 + 6 + 7.5 + 8 ) : 10 = 7.15
Variance:
(Sigma)² = ( 1.85² + 0.15² + 0.65² + 0.35² + 0.15² + 0.85² + 2.15² + 1.15² + 0.35² + 0.85² ) : 10 ≈ 1.15
Answer: C ) 1.15
erastovalidia [21]2 years ago
4 0
We have that

set of data [9, 7, 6.5, 7.5, 7, 8, 5, 6, 7.5, 8]

 step 1

Find the mean

[9+ 7+ 6.5+ 7.5+ 7+ 8+ 5+ 6+ 7.5+ 8]/10 \\ =71.5/10 \\= 7.15

 step 2

 for each number: subtract the Mean and square the result

(9-7.15) ^{2} =3.4225  \\ (9-7.15) ^{2} =3.4225  \\ (7-7.15)^{2} = 0.0225  \\ (6.5-7.15)^{2} = 0.4225  \\  (7.5-7.15)^{2} = 0.1225  \\ (7-7.15)^{2} = 0.0225 \\  (8-7.15)^{2} = 0.7225 \\ (5-7.15)^{2} = 4.6225  \\  (6-7.15)^{2} = 1.3225  \\ (7.5-7.15)^{2} = 0.1225  \\  (8-7.15)^{2} = 0.7225

Sum=11.525

 step 3

 work out the mean of those squared differences

11.525/10 \\ =1.15

this value is called the "Variance"


the answer is the option

1.15

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Let X, the number of flaws on the surface of a randomly selected boiler of a certain type, have a Poisson distribution with para
kvasek [131]

Answer:

(a) 0.932

(b) 0.0653

(c) 0.032

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(e) 0.251

Step-by-step explanation:

From the table with mean parameter μ = 5, we can compute the following cumulative and density probability

(a) P(X \leq 8) = 0.932 (cumulative)

(b) P(X = 8) = 0.0653 (density)

(c) P(9 \leq X) = 1 - P(X \leq 9) = 1 - 0.968 = 0.032 (cumulative)

(d) P(5 \leq X \leq 8) = P(X \leq 8) - P(X \leq 5) = 0.932 - 0.616 = 0.316 (cumulative)

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5 0
2 years ago
Marginal cost At a certain factory the marginal cost is 3(q-4)^2 dollars per unit when the level of production is q units.
viktelen [127]

Answer:

a.) C(q) =  -(1/4)*q^3 +  3q^2  -  12q + OH          b.) $170

Step-by-step explanation:

(a) Marginal cost is defined as the decrease or increase in total production cost if output is increased by one more unit. Mathematically:

Marginal cost (MC) = change in total cost/change in quantity

Therefore, to derive the equation for total production cost, we need to integrate the equation of marginal cost with respect to quantity. Thus:

Total cost (C) = Integral [3(q-4)^2] dq = -(1/4)*(q-4)^3 + k

where k is a constant.

The overhead (OH) = C(0) = -(1/4)*(0-4)^3 + k = -16 + k

C(q) = -(1/4)*(q^3  - 12q^2  + 48q - 64) + k = -(1/4)*q^3 +  3q^2  -  12q  -16 + k

Thus:

C(q) =  -(1/4)*q^3 +  3q^2  -  12q + OH

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7 0
1 year ago
Last year, 46% of business owners gave a holiday gift to their employees. A survey of business owners indicated that 35% plan to
DiKsa [7]

Answer:

a) Number = 60 *0.35=21

b) Since is a left tailed test the p value would be:  

p_v =P(Z  

c) If we compare the p value obtained and using the significance level given \alpha=0.05 we have p_v so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 5% the proportion of business owners providing holiday gifts had decreased from the 2008 level.  

We can use as smallest significance level 0.044 and we got the same conclusion.  

Step-by-step explanation:

Data given and notation  

n=60 represent the random sample taken

X represent the business owners plan to provide a holiday gift to their employees

\hat p=0.35 estimated proportion of business owners plan to provide a holiday gift to their employees

p_o=0.46 is the value that we want to test

\alpha=0.05 represent the significance level

Confidence=95% or 0.95

z would represent the statistic (variable of interest)

p_v represent the p value (variable of interest)  

Part a

On this case w ejust need to multiply the value of th sample size by the proportion given like this:

Number = 60 *0.35=21

2) Part b

We need to conduct a hypothesis in order to test the claim that the proportion of business owners providing holiday gifts had decreased from the 2008 level:  

Null hypothesis:p\geq 0.46  

Alternative hypothesis:p < 0.46  

When we conduct a proportion test we need to use the z statisitc, and the is given by:  

z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}} (1)  

The One-Sample Proportion Test is used to assess whether a population proportion \hat p is significantly different from a hypothesized value p_o.

Calculate the statistic  

Since we have all the info requires we can replace in formula (1) like this:  

z=\frac{0.35 -0.46}{\sqrt{\frac{0.46(1-0.46)}{60}}}=-1.710  

Statistical decision  

It's important to refresh the p value method or p value approach . "This method is about determining "likely" or "unlikely" by determining the probability assuming the null hypothesis were true of observing a more extreme test statistic in the direction of the alternative hypothesis than the one observed". Or in other words is just a method to have an statistical decision to fail to reject or reject the null hypothesis.  

The significance level provided \alpha=0.05. The next step would be calculate the p value for this test.  

Since is a left tailed test the p value would be:  

p_v =P(Z  

Part c

If we compare the p value obtained and using the significance level given \alpha=0.05 we have p_v so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 5% the proportion of business owners providing holiday gifts had decreased from the 2008 level.  

We can use as smallest significance level 0.044 and we got the same conclusion.  

8 0
2 years ago
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topjm [15]
1. You have the following information given in the problem above:

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8 0
2 years ago
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