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3 years ago

2.4 + 5.4q – 4.5q + 3.6 a.6+1.1q b.9.9q+6 c.0.9q+6 d.9.9q-6

1 answer:

8 0

You have to add the same kind of terms, in this case the ones that have a variable (5.4q and -4.5q) and the ones that don't (2.4 and 3.6), like this:

(5.4q - 4.5q) + (2.4 + 3.6) = 0.9q + 6

The answer is c. 0.9 +6

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3 years ago

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If y varies directly with x, find the missing value below. (2, -34) and (x, 85)

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Answer:

X= -5

Step-by-step explanation:

y varies directly with x,

so y=kx

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2 years ago

Underage drinking, Part I: Data collected by the Substance Abuse and Mental Health Services Administration (SAMSHA) suggests tha

dezoksy [38]

Answer:

a. Yes, there are 10 independent trials, each with exactly two possible outcomes, and a constant probability associated with each possible outcome.

b. The probability is 0.2029 or 20.29%

c. The probability is 0.2029 or 20.29%

d. The probability is 0.1671 or 16.71%

e. The probability is 0.9975 or 99.75%

Step-by-step explanation:

a. Yes, there are 10 independent trials, each with exactly two possible outcomes, and a constant probability associated with each possible outcome.

b. Let's use the binomial distribution table, this way:

Binomial distribution (n=10, p=0.697)

f(x) F(x) 1 - F(x)

x Pr[X = x] Pr[X ≤ x]

0 0.0000 0.0000

1 0.0002 0.0002

2 0.0016 0.0017

3 0.0095 0.0112

4 0.0384 0.0496

5 0.1059 0.1555

6 0.2029 0.3584

7 0.2668 0.6252

8 0.2301 0.8553

9 0.1176 0.9729

10 0.0271 1.0000

The probability is 0.2029 or 20.29%

c. If 69.7% of 18-20 years old consumed alcoholic beverages in 2008, therefore, 30.3% did not and the binomial distribution table is:

Binomial distribution (n=10, p=0.303)

f(x) F(x) 1 - F(x)

x Pr[X = x] Pr[X ≤ x]

0 0.0271 0.0271

1 0.1176 0.1447

2 0.2301 0.3748

3 0.2668 0.6416

4 0.2029 0.8445

5 0.1059 0.9504

6 0.0384 0.9888

7 0.0095 0.9983

8 0.0016 0.9998

9 0.0002 1.0000

10 0.0000 1.0000

The probability is 0.2029 or 20.29%

d. Let's use the binomial distribution table, this way:

Binomial distribution (n=5, p=0.697)

f(x) F(x) 1 - F(x)

x Pr[X = x] Pr[X ≤ x]

0 0.0026 0.0026

1 0.0294 0.0319

2 0.1351 0.1671

3 0.3109 0.4779

4 0.3576 0.8355

5 0.1645 1.0000

P(0) + P(1) + P (2) = 0.0026 + 0.0294 + 0.1351

The probability is 0.1671 or 16.71%

e. Using the same binomial distribution table we used in d. we have:

P(1) + P (2) + P(3) + P(4) + P (5) = 0.0294 + 0.1351 + 0.3109 + 0.3576 + 0.1645

The probability is 0.9975 or 99.75%

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3 years ago

Which of the following is not true about cluster sampling?

Aloiza [94]

Answer:

The correct answer is D. It is not true that cluster sampling uses randomly selected clusters and samples everyone within each cluster.

Step-by-step explanation:

Cluster sampling is a method of collecting samples and statistical data, by means of which a certain group formed by people, things, events, etc., is taken as a sample, which are not considered individually but as part of a whole, which is in turn a proportional representation of the universality of samples available in the field.

Now, since this type of sampling allows to embrace large groups of sample units, data are not always obtained from all the components of the cluster, but from those necessary to be able to quantify the desired statistics.

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2 years ago

Read 2 more answers