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Compute the sample median, 25% trimmed mean, 10% trimmed mean, and sample mean for the lifetime data given in Exercise 27, and compare these measures.

Short Answer

Expert verified

The median value is 92.The 25% trimmed mean is94.75.The 10% trimmed mean is 102.225.The sample mean is 119.26.

The highest value is observed for the sample mean as compared to all other measures. Also, as the percentage of trimmed mean increases, the value of the mean decreases.

Step by step solution

01

Given information

The data are provided consists of 50 observations, so the sample size is 50.

02

Compute sample median

Let \(\tilde x\) be the required sample median.

Since \({\bf{n = 50}}\) is even, the sample median is the average of \({\left( {\frac{{\bf{n}}}{{\bf{2}}}} \right)^{{\bf{th}}}}\) and \({\left( {\frac{{\bf{n}}}{{\bf{2}}}{\bf{ + 1}}} \right)^{{\bf{th}}}}\)term.

Calculate the sample median as follows,

\(\begin{array}{c}\tilde x &=& {\rm{average}}\,{\rm{of}}\,{\left( {\frac{n}{2}} \right)^{th}}{\rm{and}}{\left( {\frac{n}{2} + 1} \right)^{th}}{\rm{ordered}}\,{\rm{values}}\\ &=& \frac{{{x_{25}} + {x_{26}}}}{2}\end{array}\)

Substitute the values of\({x_{25}} = 91\)and\({x_{26}} = 93\)in the above formula,

\(\begin{array}{c}\tilde x &=& \frac{{91 + 93}}{2}\\ &=& \frac{{184}}{2}\\ &=& 92\end{array}\)

Thus, the sample median is 92.

03

Compute 25% trimmed mean

Let \({\bar x_{Tr}}\)be the required trimmed mean.

The number of extreme values to be trimmed are,

\(\begin{array}{c}50\left( {0.25} \right) = 12.5\\ \approx 13\end{array}\)

Thus, the smallest and largest 13 values of the data set are removed from the data set.

The remaining data for 24 valuesis as follows,

67, 68, 71, 74, 76, 78, 79, 81, 84, 85, 89, 91, 93, 96, 99, 101, 104, 105, 105, 112, 118, 123, 136, 139

The 25% trimmed mean is computed as follows,

\({\bar x_{Tr\left( {25} \right)}} = \frac{{\sum {{x_{Tr}}} }}{{{n_{Tr}}}}\)

Substitute the value of\({n_{Tr}} = 24\)in the above formula,

\(\begin{array}{c}{{\bar x}_{Tr\left( {25} \right)}} &=& \frac{{\left( {67 + 68 + 71 + 74 + \ldots + 123 + 136 + 139} \right)}}{{24}}\\ &=& \frac{{2274}}{{24}}\\ &=& 94.75\end{array}\)

Thus, the 25% trimmed mean is 94.75.

04

Compute 10% trimmed mean

Let\({\bar x_{Tr}}\)be the required trimmed mean.

The number of extreme values to be trimmed are,

\(50\left( {0.10} \right) = 5\)

Thus, the smallest and largest 5 values of the data set are removed from the data set.

The remaining data for 24 values is as follows,

36, 39, 44, 47, 50, 59, 61, 65, 67, 68, 71, 74, 76, 78, 79, 81, 84, 85, 89, 91, 93, 96, 99, 101, 104, 105, 105, 112, 118, 123, 136, 139, 141, 148, 158, 161, 168, 184, 206, 248

The trimmed mean is,

\({\bar x_{Tr\left( {10} \right)}} = \frac{{\sum {{x_{Tr}}} }}{{{n_{Tr}}}}\)

Substitute the value of\({n_{Tr}} = 40\)in the above formula,

\(\begin{array}{c}{{\bar x}_{Tr\left( {10} \right)}} &=& \frac{{\left( {36 + 39 + 44 + \ldots + 184 + 206 + 248} \right)}}{{40}}\\ &=& \frac{{4089}}{{40}}\\ &=& 102.225\end{array}\)

Thus, the 10% trimmed mean is 102.225.

05

Compute Sample Mean

Let\(\bar x\)be the required sample mean.

There are 50 observations, that is,\(n = 50\)

Sample mean formula:

\(\bar x = \frac{{\sum {{x_i}} }}{n}\)

Substitute the value of n and\(\sum {{x_i}} \)in the above formula,

\(\begin{array}{c}\bar x &=& \frac{{\left( {11 + 14 + 20 + \ldots + 322 + 388 + 513} \right)}}{{50}}\\ &=& \frac{{5963}}{{50}}\\ &=& 119.26\end{array}\)

Thus, the sample mean is 119.26.

06

 Step 6: Compare different obtained measures

As the value of sample mean is 119.26 higher than the obtained value of median, the distribution of 50 observations becomes skewed to the right or positively skewed.

The highest value is observed for sample mean as compared to all other measures. Also, as the percentage of trimmed mean increases, the value of mean decreases.

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Most popular questions from this chapter

The value of Young鈥檚 modulus (GPa) was determined forcast plates consisting of certain intermetallic substrates,resulting in the following sample observations (鈥淪trengthand Modulus of a Molybdenum-Coated Ti-25Al-10Nb-3U-1Mo Intermetallic,鈥 J. of Materials Engr.and Performance, 1997: 46鈥50):

116.4 115.9 114.6 115.2 115.8

  1. Calculate\({\bf{\bar x}}\) and the deviations from the mean.
  2. Use the deviations calculated in part (a) to obtain the sample variance and the sample standard deviation.
  3. Calculate\({{\bf{s}}^{\bf{2}}}\)by using the computational formula for the numerator \({S_{xx}}\).
  4. Subtract 100 from each observation to obtain a sample of transformed values. Now calculate the sample variance of these transformed values, and compare it to\({{\bf{s}}^{\bf{2}}}\)for the original data.

Give one possible sample of size 4 from each of the following

populations:

a. All daily newspapers published in the United States

b. All companies listed on the New York Stock Exchange

c. All students at your college or university

d. All grade point averages of students at your college or university

Using a long rod that has length \({\rm{\mu }}\)you are going to lay out a square plot in which the length of each side is \({\rm{\mu }}\).Thus the area of the plot will be \({{\rm{\mu }}^{\rm{2}}}\)However, you do not know the value of \({\rm{\mu }}\), so you decide to make \({\rm{n}}\)independent measurements \({{\rm{X}}_{\rm{1}}}{\rm{,}}{{\rm{X}}_{\rm{2}}}{\rm{, \ldots ,}}{{\rm{X}}_{\rm{n}}}\)of the length. Assume that each \({{\rm{X}}_{\rm{i}}}\)has mean \({\rm{\mu }}\) (unbiased measurements) and variance \({{\rm{\sigma }}^{\rm{2}}}\).

a. Show that \({{\rm{\bar X}}^{\rm{2}}}\)is not an unbiased estimator for \({{\rm{\mu }}^{\rm{2}}}\). (Hint: For any \({\rm{Y,E}}\left( {{{\rm{Y}}^{\rm{2}}}} \right){\rm{ = V(Y) + (E(Y)}}{{\rm{)}}^{\rm{2}}}\)Apply this with \({\rm{Y = \bar X}}\))

b. For what value of \({\rm{k}}\)is the estimator \({{\rm{\bar X}}^{\rm{2}}}{\rm{ - k}}{{\rm{S}}^{\rm{2}}}\)unbiased for \({{\rm{\mu }}^{\rm{2}}}\)? (Hint: Compute \({\rm{E}}\left( {{{{\rm{\bar X}}}^{\rm{2}}}{\rm{ - k\;}}{{\rm{S}}^{\rm{2}}}} \right)\))

The article 鈥淓ffects of Short-Term Warming on Low and High Latitude Forest Ant Communities鈥 (Ecoshpere, May 2011, Article 62) described an experiment in which observations on various characteristics were made using mini chambers of three different types: (1) cooler (PVC

frames covered with shade cloth), (2) control (PVC frames only), and (3) warmer (PVC frames covered with plastic).One of the article鈥檚 authors kindly supplied the accompanying data on the difference between air and soil temperatures(掳C).

Cooler Control Warmer

1.59 1.92 2.57

1.43 2.00 2.60

1.88 2.19 1.93

1.26 1.12 1.58

1.91 1.78 2.30

1.86 1.84 0.84

1.90 2.45 2.65

1.57 2.03 0.12

1.79 1.52 2.74

1.72 0.53 2.53

2.41 1.90 2.13

2.34 2.86

0.83 2.31

1.34 1.91

1.76

a. Compare measures of center for the three different samples.

b. Calculate, interpret, and compare the standard deviations for the three different samples.

c. Do the fourth spreads for the three samples convey the same message as do the standard deviations about relative variability?

d. Construct a comparative boxplot (which was included in the cited article) and comment on any interesting features.

a. If a constant cis added to each \({x_i}\)in a sample, yielding \({y_i} = {x_i} + c\), how do the sample mean and median of the \({y_i}'s\)relate to the mean and median of the\({x_i}'s\)? Verify your conjectures.

b. If each \({x_i}\)is multiplied by a constant c,yielding \({y_i} = c{x_i}\), answer the question of part (a). Again, verify your conjectures.

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