Un garaje rectangular tiene un perímetro de 26 metros y una superficie de 42 metros cuadrados. ¿Cuáles son las dimensiones del g
1 answer:
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Answer:
Given:
Sham: n= 20, x=0.44, s=1.24,
Magnet:n= 20, x =0.49, s= 0.95
For Sham:
Sample size, n = 20
Sample mean = 0.44
Standard deviation = 1.24
For Magnet:
Sample size = 20
Sample mean = 0.49
Standard deviation = 0.95
The null and alternative hypotheses:
H0: s1²=s2²
H1: s1² ≠ s2²
a) To find the test statistics, use the formula:
Test statistics = 1.7037
b) P-value:
Sham: degrees of freedom
Magnet: degrees of freedom
The critical values:
[Za/2, df1, df2)], [(1 - Za/2), df1, df2]
The rejection region:
Reject H0, if F < 0.3958 or if F > 2.526
c) Conclusion:
Since the critical values of test statistic is between (0.3958 < 1.7037 < 2.526), we fail to reject null hypothesis H0.
There is insufficient evidence to to support the claim that those given a sham treatment have reductions that vary more than those treated with magnets
Answer:
Yes, it would be unusual.
Step-by-step explanation:
To solve this question, we need to understand the normal probability distribution and the central limit theorem.
Normal probability distribution
Problems of normally distributed samples are solved using the z-score formula.
In a set with mean and standard deviation
, the zscore of a measure X is given by:
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.
If or
, the outcome X is considered unusual.
Central Limit Theorem
The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean and standard deviation
, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean
and standard deviation
.
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
In this question, we have that:
Would it be unusual for this sample mean to be less than 19 days?
We have to find Z when X = 19. So
By the Central Limit Theorem
, so yes, the sample mean being less than 19 days would be considered an unusual outcome.