Frequency table calculator

A frequency is the number of times a data value occurs. For example, if ten students score 90 in statistics, then score 90 has a frequency of 10. A frequency is a count of the occurrences of values within a data-set. Cumulative frequency is used to determine the number of observations below a particular value in a data set. The cumulative frequency is calculated by adding each frequency from a frequency distribution table to the sum of its predecessors. The last value will always be equal to the total for all data. A relative frequency is a frequency divided by a count of all values. Relative frequencies can be written as fractions, percents, or decimals. Cumulative relative frequency is the accumulation of the previous relative frequencies. The last value will always be equal to 1.

0-4 5-9 10-14 15-19 20-24 25-29 30-34 f: 2 4 8 6 4 3 3

Recalculate  

Calculation:

Statistical file:
{2, 2, 7, 7, 7, 7, 12, 12, 12, 12, 12, 12, 12, 12, 17, 17, 17, 17, 17, 17, 22, 22, 22, 22, 27, 27, 27, 32, 32, 32}

Frequency table :

element	frequency	cumulative frequency	relative frequency	cumulative relative frequency
2	2	2	0.066666666666667	0.066666666666667
7	4	6	0.13333333333333	0.2
12	8	14	0.26666666666667	0.46666666666667
17	6	20	0.2	0.66666666666667
22	4	24	0.13333333333333	0.8
27	3	27	0.1	0.9
32	3	30	0.1	1

Other statistical characteristics:
Average (mean): μ=16.5
Absolute deviation: 206
Mean deviation: 6.8666666666667
Minimum: 2
Maximum: 32
Variance: 70.583333333333
Standard deviation σ=8.4013887740857
Corrected sample standard deviation s=8.5450126611556
Coefficient of variation c_V=0.51787955522155
Signal-to-noise ratio SNR=1.9309509130404
Median: 17
Quartile Q1: 12
Quartile Q2: 17
Quartile Q3: 22
1st decile: 7
2nd decile: 8
3rd decile: 12
4th decile: 12
5th decile: 17
6th decile: 17
7th decile: 22
8th decile: 26
9th decile: 31.5
Interquartile range IQR: 10
Quartile Deviation QD: 5
Coefficient of Quartile Deviation CQD: 0.29411764705882
Lower fence: -3
Upper fence: 37
Set of outliers: {} - empty set - no outliers found
Interdecile range IDR: 24.5
Mode: 12 - unimodal
Geometric mean: 13.780371317329
Harmonic mean: 10.074836870588
Sum: 495
Sum of squares: 2117.5
Sum of absolute values: 495
Average absolute deviation: 6.8666666666667
Range: 30
Frequency table :

element	frequency	cumulative frequency	relative frequency	cumulative relative frequency
2	2	2	0.066666666666667	0.066666666666667
7	4	6	0.13333333333333	0.2
12	8	14	0.26666666666667	0.46666666666667
17	6	20	0.2	0.66666666666667
22	4	24	0.13333333333333	0.8
27	3	27	0.1	0.9
32	3	30	0.1	1

Z-score: {-1.7259, -1.7259, -1.1308, -1.1308, -1.1308, -1.1308, -0.5356, -0.5356, -0.5356, -0.5356, -0.5356, -0.5356, -0.5356, -0.5356, 0.0595, 0.0595, 0.0595, 0.0595, 0.0595, 0.0595, 0.6547, 0.6547, 0.6547, 0.6547, 1.2498, 1.2498, 1.2498, 1.8449, 1.8449, 1.8449}
Count items: 30

Calculation of normal distribution

Sorted statistic file: {2, 2, 7, 7, 7, 7, 12, 12, 12, 12, 12, 12, 12, 12, 17, 17, 17, 17, 17, 17, 22, 22, 22, 22, 27, 27, 27, 32, 32, 32}
Statistical file:
{2, 2, 7, 7, 7, 7, 12, 12, 12, 12, 12, 12, 12, 12, 17, 17, 17, 17, 17, 17, 22, 22, 22, 22, 27, 27, 27, 32, 32, 32}

How to enter data as a frequency table?

Simple. Write data elements (separated by spaces or commas, etc.), then write f: and further write the frequency of each data item. Each element must have a defined frequency that counts numbers before and after symbol f: must be equal. For example:

1.1 2.5 3.99
f: 5 10 15

How to enter grouped data?

Grouped data are formed by aggregating individual data into groups so that a frequency distribution of these groups serves as a convenient means of summarizing or analyzing the data.

group	frequency
10-20	5
20-30	10
30-40	15

This grouped data you can enter:
10-20 20-30 30-40
f: 5 10 15

How to enter data as a cumulative frequency table?

Similar to a frequency table, but instead, f: write cf: in the second line. For example:

10 20 30 40 50 60 70 80
cf: 5 13 20 32 60 80 90 100

The cumulative frequency is calculated by adding each frequency from a frequency distribution table to the sum of its predecessors. The last value will always equal the total for all observations since the calculator will have already added all frequencies to the previous total.