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xeze [42]
3 years ago
5

You have purchased an inexpensive USB oscilloscope (which measures and displays voltage waveforms). You wish to determine if the

oscilloscope has an error bias; in other words, you wish to determine if the errors made by the oscilloscope have a population mean that is not equal to zero. So you use a very accurate voltmeter to find the measurement errors for 13 different measurements made by your USB oscilloscope. A data file containing these measurements is HTMean1.csvPreview the document . Do a statistical analysis on this data to determine if the oscilloscope has an error bias.

Physics
1 answer:
4vir4ik [10]3 years ago
7 0

Complete Question

The complete question is shown on the first uploaded image

Answer:

1

  A

2

A

Explanation:

From the question the data given for Error (mV) is -15

-15.17

8.67

-13.74

-20.69

-6.96

-1.36

-2.96

-9.26

3.11

-14.12

6.39

-14.77

Generally

The null hypothesis is H_o : \mu =  0

The alternative hypothesis is H_a : \mu \ne  0

The sample size is n = 13

Here \mu represents the true error bias (i.e population error bias)

Generally the sample error bias is mathematically represented as

\= x  =  \frac{ \sum  x_i}{n}

=> \= x =  \frac{ -15.17  + 8.67 + (-13.74) + \cdots  + (-14.77)  }{13}

\= x =  -7.37

Generally the standard deviation is mathematically represented as

\sigma  = \sqrt{\frac{\sum (x_i - \= x )^2}{n}  }

=> \sigma  = \sqrt{\frac{ (-15.17-( -7.37) )^2 + (8.67 -( -7.37) )^2 + \cdots + (-14.77 -( -7.37) )^2 }{13}  }

=> \sigma  =  \sqrt{ 119.385}

=> \sigma  =  10.926

Generally the test statistics is mathematically represented as

t =  \frac{\= x -  \mu }{\frac{\sigma }{\sqrt{n} } }

=> t =  \frac{ -7.37 - 0 }{\frac{10.926}{\sqrt{13} } }

=> t =  -2.838

Generally the p-value is mathematically represented as

p-value  =  2 P(t < -2.432)

From the z-table  P(t < -2.432) =  0.0075

So  p-value  =  2* 0.0075

=>  p-value  = 0.015

So given that  p-value is  less than the \alpha = 0.05 then we reject the null hypothesis and conclude that the oscilloscope has an error bias

   

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