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2 years ago

⬛️ :blank divided by seven > 800

Mathematics

1 answer:

Nikolay [14]2 years ago

7 0

Answer:

7/8 is nearly 1, and 8 1/10 is obviously 8.1 (1/10), which is rounded to 8. So th expression that best estimates the products of those numbers is D, 1 * 8

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In the book Business Research Methods, Donald R. Cooper and C. William Emory (1995) discuss a manager who wishes to compare the

S_A_V [24]

Answer:

Null hypothesis is: U1 - U2 ≤ 0

Alternative hypothesis is U1 - U2 > 0

Step-by-step explanation:

The question involves a comparison of the two types of training given to the salespeople. The requirement is to set up the hypothesis that type A training leads to higher mean weakly sales compared to type B training.

Let U1 = mean sales by type A trainees

Let U2 = mean sales by type B trainees

Therefore, the null hypothesis (H0) is: U1 - U2 ≤ 0

This implies that type A training does not result in higher mean weekly sales than type B training.

The alternative hypothesis (H1) is: U1 - U2 > 0

This implies that type A training indeed results in higher mean weekly sales than type B training.

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A simple random sample of 110 analog circuits is obtained at random from an ongoing production process in which 20% of all circu

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Answer:

64.56% probability that between 17 and 25 circuits in the sample are defective.

Step-by-step explanation:

Binomial probability distribution

Probability of exactly x sucesses on n repeated trials, with p probability.

Can be approximated to a normal distribution, using the expected value and the standard deviation.

The expected value of the binomial distribution is:

$E(X) = np$

The standard deviation of the binomial distribution is:

$\sqrt{V(X)} = \sqrt{np(1-p)}$

Normal probability distribution

Problems of normally distributed samples can be solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the zscore of a measure X is given by:

$Z = \frac{X - \mu}{\sigma}$

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

When we are approximating a binomial distribution to a normal one, we have that $\mu = E(X)$ , $\sigma = \sqrt{V(X)}$ .