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kap26 [50]
3 years ago
6

Which is relatively​ better: a score of 6868 on a psychology test or a score of 5959 on an economics​ test? scores on the psycho

logy test have a mean of 8585 and a standard deviation of 1515. scores on the economics test have a mean of 6565 and a standard deviation of 1010?
Mathematics
2 answers:
kherson [118]3 years ago
8 0
The economics test score is relatively better because of its z score is greater that the z score for the psychology test.
The calculation for this question is simply;
for psychology = (68 - 85) / 15 = -1.13
for economics = (59 - 65) / 10 = -0.6
So the answer to this question is economic is relatively better.
erastovalidia [21]3 years ago
7 0

In order to get know which test is relative better, you have to use the formula to get the z score of psychology test and economics test.

Z=(raw score-sample mean)/standard deviation

Solution:

Psychology = (68 - 85) / 15 = -1.13

Economics = (59 - 65) / 10 = -0.6

Through this answer you can see that economics is closer to 0 which is the actual mean. This can be viewed through a normal distribution graph. The closer it is to 0, the relatively better it is because of it is more precise.

<span>So economics is relatively better than psychology test.</span>

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4 years ago
A manufacturer of potato chips would like to know whether its bag filling machine works correctly at the 420 gram setting. It is
anastassius [24]

Answer:

t=\frac{424-420}{\frac{26}{\sqrt{61}}}=1.202    

p_v =2*P(t_{(60)}>1.202)=0.234  

If we compare the p value and the significance level given \alpha=0.01 we see that p_v>\alpha so we can conclude that we have enough evidence to fail reject the null hypothesis, so we can conclude that the true mean is NOT different from  420. So the specification is satisfied.

Step-by-step explanation:

Data given and notation  

\bar X=424 represent the sample mean

s=26 represent the sample standard deviation

n=61 sample size  

\mu_o =420 represent the value that we want to test

\alpha=0.01 represent the significance level for the hypothesis test.  

t would represent the statistic (variable of interest)  

p_v represent the p value for the test (variable of interest)  

State the null and alternative hypotheses.  

We need to conduct a hypothesis in order to check if the true mean is different from 420 or not, the system of hypothesis would be:  

Null hypothesis:\mu = 420  

Alternative hypothesis:\mu \neq 420  

If we analyze the size for the sample is > 30 but we don't know the population deviation so is better apply a t test to compare the actual mean to the reference value, and the statistic is given by:  

t=\frac{\bar X-\mu_o}{\frac{s}{\sqrt{n}}}  (1)  

t-test: "Is used to compare group means. Is one of the most common tests and is used to determine if the mean is (higher, less or not equal) to an specified value".  

Calculate the statistic

We can replace in formula (1) the info given like this:  

t=\frac{424-420}{\frac{26}{\sqrt{61}}}=1.202    

P-value

The first step is calculate the degrees of freedom, on this case:  

df=n-1=61-1=60  

Since is a two sided test the p value would be:  

p_v =2*P(t_{(60)}>1.202)=0.234  

Conclusion  

If we compare the p value and the significance level given \alpha=0.01 we see that p_v>\alpha so we can conclude that we have enough evidence to fail reject the null hypothesis, so we can conclude that the true mean is NOT different from  420. So the specification is satisfied.

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3 years ago
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