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To find the mode of a data set, we need to determine which value(s) appear most frequently. In your sample, we have the following values:

120, 140, 115, 130, 125, 110, 135, 150, 128, 122, 117, 145, 132, 160, 113

Let's count the frequency of each value:

  • 110: 1
  • 113: 1
  • 115: 1
  • 117: 1
  • 120: 1
  • 122: 1
  • 125: 1
  • 128: 1
  • 130: 1
  • 132: 1
  • 135: 1
  • 140: 1
  • 145: 1
  • 150: 1
  • 160: 1

In this case, each value appears only once, so there is no mode in this sample. The sample is considered to be "uniform" or "uniformly distributed" because no value occurs more frequently than any other.
 
To find the mode of a data set, we need to determine which value(s) appear most frequently. In your sample, we have the following values:

120, 140, 115, 130, 125, 110, 135, 150, 128, 122, 117, 145, 132, 160, 113

Let's count the frequency of each value:

  • 110: 1
  • 113: 1
  • 115: 1
  • 117: 1
  • 120: 1
  • 122: 1
  • 125: 1
  • 128: 1
  • 130: 1
  • 132: 1
  • 135: 1
  • 140: 1
  • 145: 1
  • 150: 1
  • 160: 1

In this case, each value appears only once, so there is no mode in this sample. The sample is considered to be "uniform" or "uniformly distributed" because no value occurs more frequently than any other.
this one too
90
105
115
98
110
120
102
125
88
95
108
92
100
115
105
 
this one too
90
105
115
98
110
120
102
125
88
95
108
92
100
115
105
To find the mode of a data set, we need to determine which value(s) appear most frequently. In your sample, we have the following values:

90, 105, 115, 98, 110, 120, 102, 125, 88, 95, 108, 92, 100, 115, 105

Let's count the frequency of each value:

  • 88: 1
  • 90: 1
  • 92: 1
  • 95: 1
  • 98: 1
  • 100: 1
  • 102: 1
  • 105: 2
  • 108: 1
  • 110: 1
  • 115: 2
  • 120: 1
  • 125: 1

In this case, the values 105 and 115 appear twice, which makes them the modes of this sample. The sample is considered to have bimodal distribution since two values occur most frequently.
 
To find the mode of a data set, we need to determine which value(s) appear most frequently. In your sample, we have the following values:

90, 105, 115, 98, 110, 120, 102, 125, 88, 95, 108, 92, 100, 115, 105

Let's count the frequency of each value:

  • 88: 1
  • 90: 1
  • 92: 1
  • 95: 1
  • 98: 1
  • 100: 1
  • 102: 1
  • 105: 2
  • 108: 1
  • 110: 1
  • 115: 2
  • 120: 1
  • 125: 1

In this case, the values 105 and 115 appear twice, which makes them the modes of this sample. The sample is considered to have bimodal distribution since two values occur most frequently.
standard deviation of this sample
120, 140, 115, 130, 125, 110, 135, 150, 128, 122, 117, 145, 132, 160, 112
 
standard deviation of this sample
120, 140, 115, 130, 125, 110, 135, 150, 128, 122, 117, 145, 132, 160, 112
To calculate the standard deviation of a sample, you can follow these steps:

1. Find the mean of the sample:
Mean = (Sum of all values) / (Number of values)

2. Find the squared difference of each value from the mean:
Squared Difference = (Value - Mean)^2

3. Find the variance:
Variance = (Sum of all Squared Differences) / (Number of values)

4. Calculate the standard deviation as the square root of the variance:
Standard Deviation = √(Variance)

Let's calculate the standard deviation for the sample:
Values: 120, 140, 115, 130, 125, 110, 135, 150, 128, 122, 117, 145, 132, 160, 112

1. Calculate the mean:
Mean = (120 + 140 + 115 + 130 + 125 + 110 + 135 + 150 + 128 + 122 + 117 + 145 + 132 + 160 + 112) / 15
Mean = 1480 / 15
Mean = 98.67 (approximately)

2. Calculate the squared difference of each value from the mean:
Squared Differences:
(120 - 98.67)^2 = 409.96
(140 - 98.67)^2 = 1748.36
(115 - 98.67)^2 = 267.49
(130 - 98.67)^2 = 994.09
(125 - 98.67)^2 = 693.96
(110 - 98.67)^2 = 130.09
(135 - 98.67)^2 = 1330.56
(150 - 98.67)^2 = 2670.56
(128 - 98.67)^2 = 871.69
(122 - 98.67)^2 = 547.56
(117 - 98.67)^2 = 337.56
(145 - 98.67)^2 = 2193.16
(132 - 98.67)^2 = 1116.49
(160 - 98.67)^2 = 3761.96
(112 - 98.67)^2 = 178.89

3. Calculate the variance:
Variance = (409.96 + 1748.36 + 267.49 + 994.09 + 693.96 + 130.09 + 1330.56 + 2670.56 + 871.69 + 547.56 + 337.56 + 2193.16 + 1116.49 + 3761.96 + 178.89) / 15
Variance = 15442.97 / 15
Variance = 1029.53 (approximately)

4. Calculate the standard deviation:
Standard Deviation = √(1029.53)
Standard Deviation ≈ 32.09

Therefore, the standard deviation of the given sample is approximately 32.09.
 

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