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Leona [35]
3 years ago
5

An experiment has a single factor with eight groups and five values in each group. a. How many degrees of freedom are there in d

etermining the​ among-group variation? b. How many degrees of freedom are there in determining the​ within-group variation? c. How many degrees of freedom are there in determining the total​ variation?
Mathematics
1 answer:
pishuonlain [190]3 years ago
6 0

Answer:

A) 7

B) 32

C) 39

Step-by-step explanation:

Degree of freedom is a means of checking how many values that are free to vary, while using a statistical method.

a) since the experiment has a single factor with eight critical values. Therefore;

C - F = degree of freedom among the group variation

8 - 1 = 7

b) The degree of freedom can be calculated, if the number of data; Therefore, number of data is;

N = 8 × 5 = 40

Then the degree of freedom in determining within group variation,

N - C Therefore;

40 - 8 = 32

C) The degree of freedom in determining the total variation is,

N - 1

40 - 1 = 39

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Previous concepts  and data given  

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\bar X=1100 represent the sample mean    

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State the null and alternative hypotheses.    

We need to conduct a hypothesis in order to check if the high school students are representative of the overall population (or if the true mean is 1020 or not), the system of hypothesis would be:    

Null hypothesis:\mu = 1020    

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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{1100-1020}{\frac{144}{\sqrt{144}}}=6.67      

P-value  

First we need to calculate the degrees of freedom given by:

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Then since is a two sided test the p value would be:    

p_v =2*P(t_{144}>6.67)=2.59x10^{-10}    

Conclusion    

If we compare the p value and a significance level for example \alpha=0.05 we see that p_v so we can conclude that we have enough evidence to reject the null hypothesis, so we can conclude that the population mean is significant different from 1020 at 5% of significance.    

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