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Radda [10]
3 years ago
11

The data below shows the attendance of fans at each home game for the high school baseball team. Fan attendance at home games: 3

4, 37, 30, 65, 34, 38, 41, 33 Calculate the average attendance with and without the outlier. A. Average Attendance with the outlier: B. Average Attendance without the outlier: (Round to the nearest thenth) Question 1 options:
Mathematics
1 answer:
kogti [31]3 years ago
7 0

Answer:

Average attendance with outlier = 39

Average attendance without outlier = 35.3

Step-by-step explanation:

Given the following data 34, 37, 30, 65, 34, 38, 41, 33

The outlier is the value that is lower or higher than other values in the dataset. Hence the outlier in this case is 65

Average = Sum of data/sample size

With the outlier;

Sum of dataset =  34+37+30+65+34+38+41+33

Sum of datasets = 312

Sample size =  8

Average attendance with the outlier = 312/8

Average attendance with the outlier = 39

Without the outlier;

The required data will exclude 65;

34, 37, 30, 34, 38, 41, 33

Sum of data = 34+37+30+34+38+41+33

Sum of data = 247

Sample size = 7

Average attendance without outlier = 247/7

Average attendance without outlier = 35.3

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Answer:

9

Step-by-step explanation:

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3 years ago
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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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Answer:

Easy, all you have to do is add em all together 80+70=150 and 2+6=8 so 150+8=158

Step-by-step explanation:

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Answer:

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