Step 2: Using original number set, assign the rank value:
Since we have 4 numbers in our original number set, we assign ranks from lowest to highest (1 to 4) Our original number set in unsorted order was 17,26,42,59 Our respective ranked data set is 1,2,3,4
Root Mean Square Calculation
Root Mean Square =
√A
√N
where A = x12 + x22 + x32 + x42 and N = 4 number set items
Calculate the Median (Middle Value) Since our number set contains 4 elements which is an even number, our median number is determined as follows: Number Set = (n1,n2,n3,n4) Median Number 1 = ½(n) Median Number 1 = ½(4) Median Number 1 = Number Set Entry 2
Median Number 2 = Median Number 1 + 1 Median Number 2 = Number Set Entry 2 + 1 Median Number 2 = Number Set Entry 3
For an even number set, we average the 2 median number entries: Median = ½(n2 + n3)
Therefore, we sort our number set in ascending order and our median is the average of entry 2 and entry 3 of our number set highlighted in red: (17,26,42,59) Median = ½(26 + 42) Median = ½(68) Median = 34
The highest frequency of occurence in our number set is 1 times by the following numbers in green: (17,26,42,59) 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 + 1/x4
With N = 4 and each xi a member of the number set you entered, we have:
Let's evaluate the square difference from the mean of each term (Xi - μ)3: (X1 - μ)3 = (17 - 36)3 = -193 = -6859 (X2 - μ)3 = (26 - 36)3 = -103 = -1000 (X3 - μ)3 = (42 - 36)3 = 63 = 216 (X4 - μ)3 = (59 - 36)3 = 233 = 12167
Adding our 4 sum of cubed differences up, we have our skewness numerator: ΣE(Xi - μ)3 = -6859 + -1000 + 216 + 12167 ΣE(Xi - μ)3 = 4524
Now that we have the sum of cubed differences from the means, calculate skewness:
Skewness =
E(Xi - μ)3
(n - 1)σ3
Skewness =
4524
(4 - 1)16.01563
Skewness =
4524
(3)4107.9924850764
Skewness =
4524
12323.977455229
Skewness = 0.36708927912558
Calculate Average Deviation (Mean Absolute Deviation) denoted below:
AD =
Σ|Xi - μ|
n
Let's evaluate the absolute value of the difference from the mean of each term |Xi - μ|: |X1 - μ| = |17 - 36| = |-19| = 19 |X2 - μ| = |26 - 36| = |-10| = 10 |X3 - μ| = |42 - 36| = |6| = 6 |X4 - μ| = |59 - 36| = |23| = 23
Adding our 4 absolute value of differences from the mean, we have our average deviation numerator: Σ|Xi - μ| = 19 + 10 + 6 + 23 Σ|Xi - μ| = 58
Now that we have the absolute value of the differences from the means, calculate average deviation (mean absolute deviation):
AD =
Σ|Xi - μ|
n
AD =
58
4
Average Deviation = 14.5
Calculate the Median (Middle Value) Since our number set contains 4 elements which is an even number, our median number is determined as follows: Number Set = (n1,n2,n3,n4) Median Number 1 = ½(n) Median Number 1 = ½(4) Median Number 1 = Number Set Entry 2
Median Number 2 = Median Number 1 + 1 Median Number 2 = Number Set Entry 2 + 1 Median Number 2 = Number Set Entry 3
For an even number set, we average the 2 median number entries: Median = ½(n2 + n3)
Therefore, we sort our number set in ascending order and our median is the average of entry 2 and entry 3 of our number set highlighted in red: (17,26,42,59) Median = ½(26 + 42) Median = ½(68) Median = 34
The highest frequency of occurence in our number set is 1 times by the following numbers in green: (17,26,42,59) Since the maximum frequency of any number is 1, no mode exists. Mode = N/A
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 -58 < v < -20.5 and 79.5 < v < 117 17,26,42,59
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 < -58 or v > 117 17,26,42,59
Calculate weighted average
17,26,42,59
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 + X4p4
n
Weighted Average =
17 x 0.2 + 26 x 0.4 + 42 x 0.6 + 59 x 0.8
4
Weighted Average =
3.4 + 10.4 + 25.2 + 47.2
4
Weighted Average =
86.2
4
Weighted Average = 21.55
Frequency Distribution Table
Show the freqency distribution table for this number set
17, 26, 42, 59
Determine the Number of Intervals using Sturges Rule:
We need to choose the smallest integer k such that 2k ≥ n where n = 4
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 4
Therefore, we use 2 intervals
Our maximum value in our number set of 59 - 17 = 42
Each interval size is the difference of the maximum and minimum value divided by the number of intervals
Interval Size =
42
2
Add 1 to this giving us 21 + 1 = 22
Frequency Distribution Table
Class Limits
Class Boundaries
FD
CFD
RFD
CRFD
17 - 39
16.5 - 39.5
2
2
2/4 = 50%
2/4 = 50%
39 - 61
38.5 - 61.5
2
2 + 2 = 4
2/4 = 50%
4/4 = 100%
4
100%
Successive Ratio Calculation
Go through our 4 numbers
Determine the ratio of each number to the next one
Successive Ratio 1: 17,26,42,59
17:26 → 0.6538
Successive Ratio 2: 17,26,42,59
26:42 → 0.619
Successive Ratio 3: 17,26,42,59
42:59 → 0.7119
Successive Ratio Answer
Successive Ratio = 17:26,26:42,42:59 or 0.6538,0.619,0.7119
Final Answers
1,2,3,4 RMS = 39.401776609691 Harmonic Mean = 28.976322124924Geometric Mean = 32.35049221287 Mid-Range = 38 Weighted Average = 21.55 Successive Ratio = Successive Ratio = 17:26,26:42,42:59 or 0.6538,0.619,0.7119
You have 2 free calculationss remaining
What is the Answer?
1,2,3,4 RMS = 39.401776609691 Harmonic Mean = 28.976322124924Geometric Mean = 32.35049221287 Mid-Range = 38 Weighted Average = 21.55 Successive Ratio = Successive Ratio = 17:26,26:42,42:59 or 0.6538,0.619,0.7119
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