<-- Enter Number Set
<-- Probabilities (or counts for Weighted Average), check box if you are using these →
  

You entered a number set X of {1200,280,175}


From the 3 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

Sort Ascending from Lowest to Highest

175, 280, 1200

Rank Ascending

175 is the 1st lowest/smallest number

280 is the 2nd lowest/smallest number

1200 is the 3rd lowest/smallest number

Sort Descending from Highest to Lowest

1200, 280, 175

Rank Descending

1200 is the 1st highest/largest number

280 is the 2nd highest/largest number

175 is the 3rd highest/largest number

Ranked Data Calculation

Sort our number set in ascending order

and assign a ranking to each number:

Ranked Data Table

Number Set Value1752801200
Rank123

Step 2: Using original number set, assign the rank value:

Since we have 3 numbers in our original number set,
we assign ranks from lowest to highest (1 to 3)

Our original number set in unsorted order was 175,280,1200

Our respective ranked data set is 1,2,3

Root Mean Square Calculation

Root Mean Square  =  A
  N

where A = x12 + x22 + x32 and N = 3 number set items

Calculate A

A = 1752 + 2802 + 12002

A = 30625 + 78400 + 1440000

A = 1549025

Calculate Root Mean Square (RMS):

RMS  =  1549025
  3

RMS  =  1244.5983287792
  1.7320508075689

RMS = 718.56918015363

Central Tendency Calculation

Central tendency contains:
Mean, median, mode, harmonic mean,
geometric mean, mid-range, weighted-average:

Calculate Mean (Average) denoted as μ

μ  =  Sum of your number Set
  Total Numbers Entered

μ  =  ΣXi
  n

μ  =  175 + 280 + 1200
  3

μ  =  1655
  3

μ = 551.66666666667

Calculate the Median (Middle Value)

Since our number set contains 3 elements which is an odd number,
our median number is determined as follows:

Number Set = (n1,n2,n3)

Median Number = Entry ½(n + 1)

Median Number = Entry ½(4)

Median Number = n2

Therefore, we sort our number set in ascending order

Our median is entry 2 of our number set highlighted in red:

(175,280,1200)

Median = 280

Calculate the Mode - Highest Frequency Number

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

Calculate Harmonic Mean:

Harmonic Mean  =  N
  1/x1 + 1/x2 + 1/x3

With N = 3 and each xi a member of the number set you entered, we have:

Harmonic Mean  =  3
  1/175 + 1/280 + 1/1200

Harmonic Mean  =  3
  0.0057142857142857 + 0.0035714285714286 + 0.00083333333333333

Harmonic Mean  =  3
  0.010119047619048

Harmonic Mean = 296.47058823529

Calculate Geometric Mean:

Geometric Mean = (x1 * x2 * x3)1/N

Geometric Mean = (175 * 280 * 1200)1/3

Geometric Mean = 588000000.33333333333333

Geometric Mean = 388.85925700148

Calculate Mid-Range:

Mid-Range  =  Maximum Value in Number Set + Minimum Value in Number Set
  2

Mid-Range  =  1200 + 175
  2

Mid-Range  =  1375
  2

Mid-Range = 687.5

Stem and Leaf Plot

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

Sort our number set in descending order:

{1200,280,175}

StemLeaf
175,200
280

Basic Stats Calculations

Mean, Variance, Standard Deviation, Median, Mode

Calculate Mean (Average) denoted as μ

μ  =  Sum of your number Set
  Total Numbers Entered

μ  =  ΣXi
  n

μ  =  175 + 280 + 1200
  3

μ  =  1655
  3

μ = 551.66666666667

Calculate Variance denoted as σ2

Let's evaluate the square difference from the mean of each term (Xi - μ)2:

(X1 - μ)2 = (175 - 551.66666666667)2 = -376.666666666672 = 141877.77777778

(X2 - μ)2 = (280 - 551.66666666667)2 = -271.666666666672 = 73802.777777778

(X3 - μ)2 = (1200 - 551.66666666667)2 = 648.333333333332 = 420336.11111111

Adding our 3 sum of squared differences up

ΣE(Xi - μ)2 = 141877.77777778 + 73802.777777778 + 420336.11111111

ΣE(Xi - μ)2 = 636016.66666667

Use the sum of squared differences to calculate variance

PopulationSample

σ2  =  ΣE(Xi - μ)2
  n

σ2  =  ΣE(Xi - μ)2
  n - 1

σ2  =  636016.66666667
  3

σ2  =  636016.66666667
  2

Variance: σp2 = 212005.55555556Variance: σs2 = 318008.33333333
Standard Deviation: σp = √σp2 = √212005.55555556Standard Deviation: σs = √σs2 = √318008.33333333
Standard Deviation: σp = 460.4406Standard Deviation: σs = 563.9223

Calculate the Standard Error of the Mean:

PopulationSample

SEM  =  σp
  n

SEM  =  σs
  n

SEM  =  460.4406
  3

SEM  =  563.9223
  3

SEM  =  460.4406
  1.7320508075689

SEM  =  563.9223
  1.7320508075689

SEM = 265.8355SEM = 325.5807

Calculate Skewness:

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 = (175 - 551.66666666667)3 = -376.666666666673 = -53440629.62963

(X2 - μ)3 = (280 - 551.66666666667)3 = -271.666666666673 = -20049754.62963

(X3 - μ)3 = (1200 - 551.66666666667)3 = 648.333333333333 = 272517912.03704

Add our 3 sum of cubed differences up

ΣE(Xi - μ)3 = -53440629.62963 + -20049754.62963 + 272517912.03704

ΣE(Xi - μ)3 = 199027527.77778

Calculate skewnes

Skewness  =  E(Xi - μ)3
  (n - 1)σ3

Skewness  =  199027527.77778
  (3 - 1)460.44063

Skewness  =  199027527.77778
  (2)97615960.86267

Skewness  =  199027527.77778
  195231921.72534

Skewness = 1.0194415237984

Calculate Average Deviation (Mean Absolute Deviation) denoted below:

AD  =  Σ|Xi - μ|
  n

Evaluate the absolute value of the difference from the mean

|Xi - μ|:

|X1 - μ| = |175 - 551.66666666667| = |-376.66666666667| = 376.66666666667

|X2 - μ| = |280 - 551.66666666667| = |-271.66666666667| = 271.66666666667

|X3 - μ| = |1200 - 551.66666666667| = |648.33333333333| = 648.33333333333

Average deviation numerator:

Σ|Xi - μ| = 376.66666666667 + 271.66666666667 + 648.33333333333

Σ|Xi - μ| = 1296.6666666667

Calculate average deviation (mean absolute deviation)

AD  =  Σ|Xi - μ|
  n

AD  =  1296.6666666667
  3

Average Deviation = 432.22222

Calculate the Median (Middle Value)

Since our number set contains 3 elements which is an odd number,
our median number is determined as follows:

Number Set = (n1,n2,n3)

Median Number = Entry ½(n + 1)

Median Number = Entry ½(4)

Median Number = n2

Therefore, we sort our number set in ascending order

Our median is entry 2 of our number set highlighted in red:

(175,280,1200)

Median = 280

Calculate the Mode - Highest Frequency Number

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

Calculate the Range

Range = Largest Number in the Number Set - Smallest Number in the Number Set

Range = 1200 - 175

Range = 1025

Calculate Pearsons Skewness Coefficient 1:

PSC1  =  μ - Mode
  σ

PSC1  =  3(551.66666666667 - N/A)
  460.4406

Since no mode exists, we do not have a Pearsons Skewness Coefficient 1

Calculate Pearsons Skewness Coefficient 2:

PSC2  =  μ - Median
  σ

PSC1  =  3(551.66666666667 - 280)
  460.4406

PSC2  =  3 x 271.66666666667
  460.4406

PSC2  =  815
  460.4406

PSC2 = 1.77

Calculate Entropy:

Entropy = Ln(n)

Entropy = Ln(3)

Entropy = 1.0986122886681

Calculate Mid-Range:

Mid-Range  =  Smallest Number in the Set + Largest Number in the Set
  2

Mid-Range  =  1200 + 175
  2

Mid-Range  =  1375
  2

Mid-Range = 687.5

Calculate the Quartile Items

We need to sort our number set from lowest to highest shown below:

{175,280,1200}

Calculate Upper Quartile (UQ) when y = 75%:

V  =  y(n + 1)
  100

V  =  75(3 + 1)
  100

V  =  75(4)
  100

V  =  300
  100

V = 3 ← Rounded down to the nearest integer

Upper quartile (UQ) point = Point # 3 in the dataset which is 1200

175,280,1200

Calculate Lower Quartile (LQ) when y = 25%:

V  =  y(n + 1)
  100

V  =  25(3 + 1)
  100

V  =  25(4)
  100

V  =  100
  100

V = 1 ← Rounded up to the nearest integer

Lower quartile (LQ) point = Point # 1 in the dataset which is 175

175,280,1200

Calculate Inter-Quartile Range (IQR):

IQR = UQ - LQ

IQR = 1200 - 175

IQR = 1025

Calculate Lower Inner Fence (LIF):

Lower Inner Fence (LIF) = LQ - 1.5 x IQR

Lower Inner Fence (LIF) = 175 - 1.5 x 1025

Lower Inner Fence (LIF) = 175 - 1537.5

Lower Inner Fence (LIF) = -1362.5

Calculate Upper Inner Fence (UIF):

Upper Inner Fence (UIF) = UQ + 1.5 x IQR

Upper Inner Fence (UIF) = 1200 + 1.5 x 1025

Upper Inner Fence (UIF) = 1200 + 1537.5

Upper Inner Fence (UIF) = 2737.5

Calculate Lower Outer Fence (LOF):

Lower Outer Fence (LOF) = LQ - 3 x IQR

Lower Outer Fence (LOF) = 175 - 3 x 1025

Lower Outer Fence (LOF) = 175 - 3075

Lower Outer Fence (LOF) = -2900

Calculate Upper Outer Fence (UOF):

Upper Outer Fence (UOF) = UQ + 3 x IQR

Upper Outer Fence (UOF) = 1200 + 3 x 1025

Upper Outer Fence (UOF) = 1200 + 3075

Upper Outer Fence (UOF) = 4275

Calculate Suspect Outliers:

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 -2900 < v < -1362.5 and 2737.5 < v < 4275

175,280,1200

Calculate Highly Suspect Outliers:

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 < -2900 or v > 4275

175,280,1200

Calculate weighted average

175, 280, 1200

Weighted-Average Formula:

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
  n

Weighted Average  =  175 x 0.2 + 280 x 0.4 + 1200 x 0.6
  3

Weighted Average  =  35 + 112 + 720
  3

Weighted Average  =  867
  3

Weighted Average = 289

Frequency Distribution Table

Show the freqency distribution table for this number set

175, 280, 1200

Determine the Number of Intervals using Sturges Rule:

We need to choose the smallest integer k such that 2k ≥ n where n = 3

For k = 1, we have 21 = 2

For k = 2, we have 22 = 4 ← Use this since it is greater than our n value of 3

Therefore, we use 2 intervals

Our maximum value in our number set of 1200 - 175 = 1025

Each interval size is the difference of the maximum and minimum value divided by the number of intervals

Interval Size  =  1025
  2

Add 1 to this giving us 512 + 1 = 513

Frequency Distribution Table

Class LimitsClass BoundariesFDCFDRFDCRFD
175 - 688174.5 - 688.5222/3 = 66.67%2/3 = 66.67%
688 - 1201687.5 - 1201.512 + 1 = 31/3 = 33.33%3/3 = 100%
  3 100% 

Successive Ratio Calculation

Go through our 3 numbers

Determine the ratio of each number to the next one

Successive Ratio 1: 175,280,1200

175:280 → 0.625

Successive Ratio 2: 175,280,1200

280:1200 → 0.2333

Successive Ratio Answer

Successive Ratio = 175:280,280:1200 or 0.625,0.2333

Final Answers


1,2,3
RMS = 718.56918015363
Harmonic Mean = 296.47058823529Geometric Mean = 388.85925700148
Mid-Range = 687.5
Weighted Average = 289
Successive Ratio = Successive Ratio = 175:280,280:1200 or 0.625,0.2333


Download the mobile appGenerate a practice problemGenerate a quiz

Common Core State Standards In This Lesson
6.SP.A.2, 6.SP.A.3, 6.SP.B.5, 6.SP.B.5.A, 6.SP.B.5.B, 6.SP.B.5.C, 6.SP.B.5.D, 7.SP.A.1, 7.SP.A.2, 7.SP.B.3, 7.SP.B.4, HSS.ID.A.2, HSS.ID.A.4, HSS.MD.A.2
What is the Answer?
1,2,3
RMS = 718.56918015363
Harmonic Mean = 296.47058823529Geometric Mean = 388.85925700148
Mid-Range = 687.5
Weighted Average = 289
Successive Ratio = Successive Ratio = 175:280,280:1200 or 0.625,0.2333
How does the Basic Statistics Calculator work?
Free Basic Statistics Calculator - Given a number set, and an optional probability set, this calculates the following statistical items:
Expected Value
Mean = μ
Variance = σ2
Standard Deviation = σ
Standard Error of the Mean
Skewness
Mid-Range
Average Deviation (Mean Absolute Deviation)
Median
Mode
Range
Pearsons Skewness Coefficients
Entropy
Upper Quartile (hinge) (75th Percentile)
Lower Quartile (hinge) (25th Percentile)
InnerQuartile Range
Inner Fences (Lower Inner Fence and Upper Inner Fence)
Outer Fences (Lower Outer Fence and Upper Outer Fence)
Suspect Outliers
Highly Suspect Outliers
Stem and Leaf Plot
Ranked Data Set
Central Tendency Items such as Harmonic Mean and Geometric Mean and Mid-Range
Root Mean Square
Weighted Average (Weighted Mean)
Frequency Distribution
Successive Ratio
This calculator has 2 inputs.
What 8 formulas are used for the Basic Statistics Calculator?
Root Mean Square = √A/√N
Successive Ratio = n1/n0
μ = ΣXi/n
Mode = Highest Frequency Number
Mid-Range = (Maximum Value in Number Set + Minimum Value in Number Set)/2
Quartile: V = y(n + 1)/100
σ2 = ΣE(Xi - μ)2/n
What 20 concepts are covered in the Basic Statistics Calculator?
average deviation
Mean of the absolute values of the distance from the mean for each number in a number set
basic statistics
central tendency
a central or typical value for a probability distribution. Typical measures are the mode, median, mean
entropy
refers to disorder or uncertainty
expected value
predicted value of a variable or event
E(X) = ΣxI · P(x)
frequency distribution
frequency measurement of various outcomes
inner fence
ut-off values for upper and lower outliers in a dataset
mean
A statistical measurement also known as the average
median
the value separating the higher half from the lower half of a data sample,
mode
the number that occurs the most in a number set
outer fence
start with the IQR and multiply this number by 3. We then subtract this number from the first quartile and add it to the third quartile. These two numbers are our outer fences.
outlier
an observation that lies an abnormal distance from other values in a random sample from a population
quartile
1 of 4 equal groups in the distribution of a number set
range
Difference between the largest and smallest values in a number set
rank
the data transformation in which numerical or ordinal values are replaced by their rank when the data are sorted.
sample space
the set of all possible outcomes or results of that experiment.
standard deviation
a measure of the amount of variation or dispersion of a set of values. The square root of variance
stem and leaf plot
a technique used to classify either discrete or continuous variables. A stem and leaf plot is used to organize data as they are collected. A stem and leaf plot looks something like a bar graph. Each number in the data is broken down into a stem and a leaf, thus the name.
variance
How far a set of random numbers are spead out from the mean
weighted average
An average of numbers using probabilities for each event as a weighting
Example calculations for the Basic Statistics Calculator
Basic Statistics Calculator Video

Tags:



Add This Calculator To Your Website