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2 years ago

4 In

Mathematics

1 answer:

Ad libitum [116K]2 years ago

3 0

Answer:

32 in

Step-by-step explanation:

Volume= 1/2 a•c•h

=1/2•4•4•4

= 32 in

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Consider the following hypothesis test: H 0: 20 H a: < 20 A sample of 60 provided a sample mean of 19.5. The population stand

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Answer:

We reject the null hypothesis and accept the alternate hypothesis. Thus, it be concluded that the population mean is less than 20.

Step-by-step explanation:

We are given the following in the question:

Population mean, μ = 60

Sample mean, $\bar{x}$ = 19.5

Sample size, n = 60

Alpha, α = 0.05

Population standard deviation, σ = 1.8

First, we design the null and the alternate hypothesis

$H_{0}: \mu = 20\\H_A: \mu < 20$

We use One-tailed z test to perform this hypothesis.

Formula:

$z_{stat} = \displaystyle\frac{\bar{x} - \mu}{\frac{\sigma}{\sqrt{n}} }$

Putting all the values, we have

$z_{stat} = \displaystyle\frac{19.5 - 20}{\frac{1.8}{\sqrt{60}} } = -2.151$

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Since,

$z_{stat} < z_{critical}$

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3 years ago

Calculating the degrees of freedom, the sample variance, and the estimated standard error for evaluations using the t statistic

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Answer:

a) For the first part we have a sample of n =10 and we want to find the degrees of freedom, and we can use the following formula:

$df = n-1= 10-1=9$

d.9

b) $s^2 = \frac{SS}{n-1}= \frac{600}{41-1}= 15$

a.15

c) For this case we have the sample size n = 25 and the sample variance is $s^2 =400$ , the standard error can founded with this formula:

$SE = \frac{s^2}{\sqrt{n}}= \frac{400}{\sqrt{25}}= 80$

Step-by-step explanation:

Part a

For the first part we have a sample of n =10 and we want to find the degrees of freedom, and we can use the following formula:

$df = n-1= 10-1=9$

d.9

Part b

From a sample we know that n=41 and SS= 600, where SS represent the sum of quares given by:

$SS = \sum_{i=1}^n (X_i -\bar X)^2$

And the sample variance for this case can be calculated from this formula:

$s^2 = \frac{SS}{n-1}= \frac{600}{41-1}= 15$

a.15

Part c

For this case we have the sample size n = 25 and the sample variance is $s^2 =400$ , the standard error can founded with this formula:

$SE = \frac{s^2}{\sqrt{n}}= \frac{400}{\sqrt{25}}= 80$

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