You entered a number set X of {20,40,10,200,50}
From the 5 numbers you entered, we want to calculate the mean, variance, standard deviation, standard error of the mean, skewness, average deviation (mean absolute deviation), median, mode, range, Pearsons Skewness Coefficient of that number set, entropy, mid-range
10, 20, 40, 50, 200
Rank Ascending
10 is the 1st lowest/smallest number
20 is the 2nd lowest/smallest number
40 is the 3rd lowest/smallest number
50 is the 4th lowest/smallest number
200 is the 5th lowest/smallest number
200, 50, 40, 20, 10
Rank Descending
200 is the 1st highest/largest number
50 is the 2nd highest/largest number
40 is the 3rd highest/largest number
20 is the 4th highest/largest number
10 is the 5th highest/largest number
Sort our number set in ascending order
and assign a ranking to each number:
Number Set Value | 10 | 20 | 40 | 50 | 200 |
Rank | 1 | 2 | 3 | 4 | 5 |
Since we have 5 numbers in our original number set,
we assign ranks from lowest to highest (1 to 5)
Our original number set in unsorted order was 10,20,40,50,200
Our respective ranked data set is 1,2,3,4,5
Root Mean Square = | √A |
√N |
where A = x12 + x22 + x32 + x42 + x52 and N = 5 number set items
A = 102 + 202 + 402 + 502 + 2002
A = 100 + 400 + 1600 + 2500 + 40000
A = 44600
RMS = | √44600 |
√5 |
RMS = | 211.18712081943 |
2.2360679774998 |
RMS = 94.445751624941
Central tendency contains:
Mean, median, mode, harmonic mean,
geometric mean, mid-range, weighted-average:
μ = | Sum of your number Set |
Total Numbers Entered |
μ = | ΣXi |
n |
μ = | 10 + 20 + 40 + 50 + 200 |
5 |
μ = | 320 |
5 |
μ = 64
Since our number set contains 5 elements which is an odd number,
our median number is determined as follows:
Number Set = (n1,n2,n3,n4,n5)
Median Number = Entry ½(n + 1)
Median Number = Entry ½(6)
Median Number = n3
Our median is entry 3 of our number set highlighted in red:
(10,20,40,50,200)
Median = 40
The highest frequency of occurence in our number set is 1 times
by the following numbers in green:
()
Since the maximum frequency of any number is 1, no mode exists.
Mode = N/A
Harmonic Mean = | N |
1/x1 + 1/x2 + 1/x3 + 1/x4 + 1/x5 |
With N = 5 and each xi a member of the number set you entered, we have:
Harmonic Mean = | 5 |
1/10 + 1/20 + 1/40 + 1/50 + 1/200 |
Harmonic Mean = | 5 |
0.1 + 0.05 + 0.025 + 0.02 + 0.005 |
Harmonic Mean = | 5 |
0.2 |
Harmonic Mean = 25
Geometric Mean = (x1 * x2 * x3 * x4 * x5)1/N
Geometric Mean = (10 * 20 * 40 * 50 * 200)1/5
Geometric Mean = 800000000.2
Geometric Mean = 38.073078774318
Mid-Range = | Maximum Value in Number Set + Minimum Value in Number Set |
2 |
Mid-Range = | 200 + 10 |
2 |
Mid-Range = | 210 |
2 |
Mid-Range = 105
Take the first digit of each value in our number set
Use this as our stem value
Use the remaining digits for our leaf portion
{200,50,40,20,10}
Stem | Leaf |
---|---|
2 | 00,0 |
5 | 0 |
4 | 0 |
1 | 0 |
Let's evaluate the square difference from the mean of each term (Xi - μ)2:
(X1 - μ)2 = (10 - 64)2 = -542 = 2916
(X2 - μ)2 = (20 - 64)2 = -442 = 1936
(X3 - μ)2 = (40 - 64)2 = -242 = 576
(X4 - μ)2 = (50 - 64)2 = -142 = 196
(X5 - μ)2 = (200 - 64)2 = 1362 = 18496
ΣE(Xi - μ)2 = 2916 + 1936 + 576 + 196 + 18496
ΣE(Xi - μ)2 = 24120
Population | Sample | ||||||||
---|---|---|---|---|---|---|---|---|---|
|
|
|
| ||||||
Variance: σp2 = 4824 | Variance: σs2 = 6030 | ||||||||
Standard Deviation: σp = √σp2 = √4824 | Standard Deviation: σs = √σs2 = √6030 | ||||||||
Standard Deviation: σp = 69.455 | Standard Deviation: σs = 77.6531 |
Population | Sample | ||||||||
---|---|---|---|---|---|---|---|---|---|
|
|
|
|
|
| ||||
SEM = 31.0612 | SEM = 34.7275 |
Skewness = | E(Xi - μ)3 |
(n - 1)σ3 |
Let's evaluate the square difference from the mean of each term (Xi - μ)3:
(X1 - μ)3 = (10 - 64)3 = -543 = -157464
(X2 - μ)3 = (20 - 64)3 = -443 = -85184
(X3 - μ)3 = (40 - 64)3 = -243 = -13824
(X4 - μ)3 = (50 - 64)3 = -143 = -2744
(X5 - μ)3 = (200 - 64)3 = 1363 = 2515456
ΣE(Xi - μ)3 = -157464 + -85184 + -13824 + -2744 + 2515456
ΣE(Xi - μ)3 = 2256240
Skewness = | E(Xi - μ)3 |
(n - 1)σ3 |
Skewness = | 2256240 |
(5 - 1)69.4553 |
Skewness = | 2256240 |
(4)335050.71337137 |
Skewness = | 2256240 |
1340202.8534855 |
Skewness = 1.6835063394561
AD = | Σ|Xi - μ| |
n |
Evaluate the absolute value of the difference from the mean
|Xi - μ|:
|X1 - μ| = |10 - 64| = |-54| = 54
|X2 - μ| = |20 - 64| = |-44| = 44
|X3 - μ| = |40 - 64| = |-24| = 24
|X4 - μ| = |50 - 64| = |-14| = 14
|X5 - μ| = |200 - 64| = |136| = 136
Σ|Xi - μ| = 54 + 44 + 24 + 14 + 136
Σ|Xi - μ| = 272
Calculate average deviation (mean absolute deviation)
AD = | Σ|Xi - μ| |
n |
AD = | 272 |
5 |
Average Deviation = 54.4
Range = Largest Number in the Number Set - Smallest Number in the Number Set
Range = 200 - 10
Range = 190
PSC1 = | μ - Mode |
σ |
PSC1 = | 3(64 - N/A) |
69.455 |
Since no mode exists, we do not have a Pearsons Skewness Coefficient 1
PSC2 = | μ - Median |
σ |
PSC1 = | 3(64 - 40) |
69.455 |
PSC2 = | 3 x 24 |
69.455 |
PSC2 = | 72 |
69.455 |
PSC2 = 1.0366
Entropy = Ln(n)
Entropy = Ln(5)
Entropy = 1.6094379124341
Mid-Range = | Smallest Number in the Set + Largest Number in the Set |
2 |
Mid-Range = | 200 + 10 |
2 |
Mid-Range = | 210 |
2 |
Mid-Range = 105
We need to sort our number set from lowest to highest shown below:
{10,20,40,50,200}
V = | y(n + 1) |
100 |
V = | 75(5 + 1) |
100 |
V = | 75(6) |
100 |
V = | 450 |
100 |
V = 4 ← Rounded down to the nearest integer
Upper quartile (UQ) point = Point # 4 in the dataset which is 50
10,20,40,50,200V = | y(n + 1) |
100 |
V = | 25(5 + 1) |
100 |
V = | 25(6) |
100 |
V = | 150 |
100 |
V = 2 ← Rounded up to the nearest integer
Lower quartile (LQ) point = Point # 2 in the dataset which is 20
10,20,40,50,200
IQR = UQ - LQ
IQR = 50 - 20
IQR = 30
Lower Inner Fence (LIF) = LQ - 1.5 x IQR
Lower Inner Fence (LIF) = 20 - 1.5 x 30
Lower Inner Fence (LIF) = 20 - 45
Lower Inner Fence (LIF) = -25
Upper Inner Fence (UIF) = UQ + 1.5 x IQR
Upper Inner Fence (UIF) = 50 + 1.5 x 30
Upper Inner Fence (UIF) = 50 + 45
Upper Inner Fence (UIF) = 95
Lower Outer Fence (LOF) = LQ - 3 x IQR
Lower Outer Fence (LOF) = 20 - 3 x 30
Lower Outer Fence (LOF) = 20 - 90
Lower Outer Fence (LOF) = -70
Upper Outer Fence (UOF) = UQ + 3 x IQR
Upper Outer Fence (UOF) = 50 + 3 x 30
Upper Outer Fence (UOF) = 50 + 90
Upper Outer Fence (UOF) = 140
Suspect Outliers are values between the inner and outer fences
We wish to mark all values in our dataset (v) in red below such that -70 < v < -25 and 95 < v < 140
10,20,40,50,200
Highly Suspect Outliers are values outside the outer fences
We wish to mark all values in our dataset (v) in red below such that v < -70 or v > 140
10,20,40,50,200
10, 20, 40, 50, 200
Multiply each value by each probability amount
We do this by multiplying each Xi x pi to get a weighted score Y
Weighted Average = | X1p1 + X2p2 + X3p3 + X4p4 + X5p5 |
n |
Weighted Average = | 10 x 0.2 + 20 x 0.4 + 40 x 0.6 + 50 x 0.8 + 200 x 0.9 |
5 |
Weighted Average = | 2 + 8 + 24 + 40 + 180 |
5 |
Weighted Average = | 254 |
5 |
Weighted Average = 50.8
Show the freqency distribution table for this number set
10, 20, 40, 50, 200
We need to choose the smallest integer k such that 2k ≥ n where n = 5
For k = 1, we have 21 = 2
For k = 2, we have 22 = 4
For k = 3, we have 23 = 8 ← Use this since it is greater than our n value of 5
Therefore, we use 3 intervals
Our maximum value in our number set of 200 - 10 = 190
Each interval size is the difference of the maximum and minimum value divided by the number of intervals
Interval Size = | 190 |
3 |
Add 1 to this giving us 63 + 1 = 64
Class Limits | Class Boundaries | FD | CFD | RFD | CRFD |
---|---|---|---|---|---|
10 - 74 | 9.5 - 74.5 | 4 | 4 | 4/5 = 80% | 4/5 = 80% |
74 - 138 | 73.5 - 138.5 | 4 + = 4 | /5 = 0% | 4/5 = 80% | |
138 - 202 | 137.5 - 202.5 | 1 | 4 + + 1 = 5 | 1/5 = 20% | 5/5 = 100% |
5 | 100% |
Go through our 5 numbers
Determine the ratio of each number to the next one
10:20 → 0.5
20:40 → 0.5
40:50 → 0.8
50:200 → 0.25
Successive Ratio = 10:20,20:40,40:50,50:200 or 0.5,0.5,0.8,0.25