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Zarrin [17]
3 years ago
11

Consider the following hypothesis test:H0: 20Ha: < 20A sample of 60 provided a sample mean of 19.6. The population standard d

eviation is 1.6.A sample of 60 provided a sample mean of 19.6. The population standard deviation is 1.6.a. Compute the value of the test statistic (to 2 decimals). If your answer is negative, use minus "-" sign.b. What is the p-value (to 3 decimals)?d. Using = .05, what is the critical value for the test statistic (to 3 decimals)? If your answer is negative, use minus "-" sign. _______What is the rejection rule using the critical value?Reject H0 if z ____ _____

Mathematics
1 answer:
elixir [45]3 years ago
4 0

Answer:

a: z = -1.936

b: 0.0265

d: z < -1.645

Reject H0 if z < -1.645

Step-by-step explanation:

We are given:

H0:  µ = 20

HA:  µ < 20

n = 60, sample mean: 19.6, σ = 1.6

Since the alternate hypothesis has a < sign in it, it is a left tailed test.  The < or > sign in the alternate hypothesis points towards the rejection region.

For a:  We need to calculate the test statistic for our situation.  This is done with a z-score formula for samples.  

For b:  we need to use the z-score table to look up the p-value for the score we calculate in part a.  The p-value is 0.0265.  This means that there is only about a 2.65% chance that the sample values were a result of random chance.

For d:  Since the significance level is 0.05, and this is a one tailed test, we have a critical value of z < - 1.645.  This means that if the z-score we calculate in part a is less than -1.645, we will reject the null hypothesis

See attached photo for all the calculations!

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Answer:

Step-by-step explanation:

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2 years ago
Persons having Raynaud's syndrome are apt to suffer a sudden impairment of blood circulation in fingers and toes. In an experime
Citrus2011 [14]

Answer:

There is enough evidence to say that the true average heat output of persons with the syndrmoe differs from the true average heat output of non-sufferers.

Step-by-step explanation:

We have to perform a hypothesis test on the difference between means.

The null and alternative hypothesis are:

H_0: \mu_1-\mu_2=0\\\\H_a: \mu_1-\mu_2

μ1: mean heat output for subjects with the syndrome.

μ2: mean heat output for non-sufferers.

We will use a significance level of 0.05.

The difference between sample means is:

M_d=\bar x_1-\bar x_2=0.63-2.09=-1.46

The standard error is

s_{M_d}=\sqrt{\sigma_1^2/n_1+\sigma_2^2/n_2}=\sqrt{0.3^2/9+0.5^2/9}=\sqrt{ 0.038 } \\\\ s_{M_d}=0.194

The t-statistic is

t=\dfrac{M_d}{s_{M_d}}=\dfrac{-1.46}{0.194}=-7.52

The degrees of freedom are

df=n_1+n_2-2=9+9-2=16

The critical value for a left tailed test at a significance level of 0.05 and 16 degrees of freedom is t=-1.746.

The t-statistic is below the critical value, so it lies in the rejection region.

The null hypothesis is rejected.

There is enough evidence to say that the true average heat output of persons with the syndrmoe differs from the true average heat output of non-sufferers.

5 0
3 years ago
It's nothing new: Let's recap rounding to the nearest 100<br>61566=<br>70284=​
kap26 [50]

Answer:

Step-by-step explanation:

61566= 61600

70284= 70300

<h2><em>hope this helps comment if/if not </em></h2>
8 0
2 years ago
31. A business rents cars for $150 a day and vans for $300 a day. One day it rented a total of 30 vehicles and
Advocard [28]

Answer:

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Step-by-step explanation:

1. You multiply 22 x 150 = 3,300.

2. Then you multiply 300 x 8 = 2,400.

3. Next, add 3,300 + 2,400

4. That equals 5700.

Hopefully, that helps!

7 0
3 years ago
In a study of 250 adults, the mean heart rate was 70 beats per minute. Assume the population of heart rates is known to be appro
klasskru [66]
This is a good question!

The steps are like follows:

Form the confidence level (99%), we calculate the "alpha" value
alpha=1-(99/100)=0.01

Now, calculate the critical probability (p-start)
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z-score could be calculated from p*,,,
z-score=<span>2.57583
(http://www.socscistatistics.com/tests/ztest/zscorecalculator.aspx)

Now, calculate the Margin of Error:
</span>standard<span> deviation = s
number of adults = n
</span><span>
ME=(z*s)/(sqrt n)=(</span><span>2.57583*12)/(sqrt 250) = 1.955

The confidence interval = mean +or- ME
                                      = 70+1.955</span>  or  70-1.955


So that we can conclude that <span>the 99% confidence interval for the mean beats per minute is 68.045 and 71.955

</span>

I hope you got the idea!

If you still need help, just let me know!





4 0
3 years ago
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