Last updated on June 18th, 2025
The step deviation method is a shortcut technique for finding the mean of grouped data more efficiently and easily. It simplifies the calculations of larger datasets and is especially useful when the class intervals are uniform. Let us see more about step deviation method and how it is used in the topic below.
The step deviation method is a statistical technique that is used to calculate the mean of a grouped data efficiently and easily. It simplifies the calculation by selecting an assumed mean, determining the class midpoints and class width to standardize deviations. This method reduces the larger numbers into manageable values. This makes it useful for datasets with uniform class intervals.
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The formula for Step deviation is given below:
Mean = A + c (Σfiui / Σfi)
Where,
c is the class width
A is the assumed mean
Σfiui is the sum of the product of frequency and deviation values
Σfi is the number of frequencies.
To use step deviation, we must follow the following steps:
Step 1: Create a table containing 5 columns: class interval, class marks (xi), deviations di = xi - A, the values of ui = di/h, and frequencies.
Step 2: Find the mean:
∑xiui / ∑ui
Step 3: Calculate the mean by adding the assumed mean A to the product of the class width h with mean of ui.
The step deviation method have numerous applications across various fields. Let us explore how the step deviation method is used in different areas:
Students tend to make some mistakes while solving problems related to step deviation method. Let us now see the different types of mistakes students make while solving problems related to step deviation method and their solutions:
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Given the following frequency distribution, find the mean.
The mean is approximately 31.56.
Determine midpoint:
10–20: 15
20–30: 25
30–40: 35
40–50: 45
Selecting assumed mean:
Choose a = 35
Class width:
h = 10
Calculate step deviations:
For 15: u = (15-35)/10 = -2
For 25: u = (25-35)/10 = -1
For 35: u = (35-35)/10 = 0
For 45: u = (45-35)/10 = 1
Compute: f and fu:
f = 5 + 8 + 12 + 7 = 32
fu = 5(-2) + 8(-1) + 12(0) + 7(1) = -10 - 8 + 0 + 7 = -11
Calculate the mean:
x = 35 + 10 (-11/32) = 35 – (110/32) 35 – 3.44 = 31.56.
Compute the mean from the grouped data below.
The mean is approximately 21.36.
Midpoints:
5, 15, 25, 35
Assumed mean a = 15
Class width h = 10
Step deviations:
For 5: u = (5-15)/10 = -1
For 15: u = 0
For 25: u = 1
For 35: u = 2
Sums:
f = 3 + 6 + 9 + 4 = 22
fu = 3(-1) + 6(0) + 9(1) + 4(2) = -3 + 0 + 9 + 8 = 14
Mean:
x = 15 + 10 (14/22) 15 + 6.36 = 21.36.
Calculate the mean for the distribution below.
The mean is approximately 61.89.
Midpoints:
45, 55, 65, 75
Assumed mean a = 65
Class width h = 10
Step deviations:
For 5: u = (45-65)/10 = -2
For 15: u = -1
For 25: u = 0
For 35: u = 1
Sums:
f = 8 + 10 + 15 + 12 = 45
fu = 8(-2) + 10(-1) + 15(0) + 12(1) = -16 - 10 + 0 + 12 = -14
Mean:
x = 65 + 10 (-14/45) 65 - 3.11 = 61.89.
Find the mean using the following grouped data.
The mean is approximately 40.71.
Midpoints:
25, 35, 45, 55
Assumed mean a = 35
Class width h = 10
Step deviations:
For 5: u = (25-35)/10 = -1
For 15: u = 0
For 25: u = 1
For 35: u = 2
Sums:
f = 4 + 10 + 8 + 6 = 28.
fu = 4(-1) + 10(0) + 8(1) + 6(2) = -4 + 0 + 8 + 12 = 16
Mean:
x = 35 + 10 (16/28) 35 + 5.71 = 40.71.
Determine the mean for the following distribution.
The mean is approximately 117.60.
Midpoints:
105, 115, 125, 135
Assumed mean a = 125
Class width h = 10
Step deviations:
For 105: u = (105-125)/10 = -2
For 115: u = -1
For 125: u = 0
For 135: u = 1
Sums:
f = 12 + 18 + 15 + 5 = 50.
fu = 12(-2) + 18(-1) + 15(0) + 5(1) = -24 - 18 + 0 + 5 = -37
Mean:
x = 125 + 10 (-37/28) 125 - 7.40 = 117.6.
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Jaipreet Kour Wazir is a data wizard with over 5 years of expertise in simplifying complex data concepts. From crunching numbers to crafting insightful visualizations, she turns raw data into compelling stories. Her journey from analytics to education ref
: She compares datasets to puzzle games—the more you play with them, the clearer the picture becomes!