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STATISTICAL TREATMENT OF DATA
Statistical treatment of data is essential to make use of the data in the right
form. Raw data collection is only one aspect of any experiment. The organization of
data is equally important so that appropriate conclusions can be drawn. (Siddharta
Kalla, 2009)
1. Frequency and Percentage Distribution
A frequency and percentage distribution is a display of data that specifies the
percentage of observations that exist for each data point or grouping of data points.
The process of creating frequency and percentage distribution involves identifying
the total number of observations to be presented and counting the total number of
observations within each data point or grouping of data points.
FORMULA:
Where:
P = percentage
F = frequency
N = number of respondent
100x
N
f
P 
2. Weighted Mean
A weighted mean is a kind of average. Instead of each data point
contributing equally to the final mean, some data points contribute more weight than
others. (Andale, 2014)
Formula:
x̅ =
∑[( 𝑓)( 𝑤)]
𝑛
Where:
x̅ = weighted mean
F = frequencies to the given
W = weights
n =total number of respondents

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Statistical treatment of data

  • 1. STATISTICAL TREATMENT OF DATA Statistical treatment of data is essential to make use of the data in the right form. Raw data collection is only one aspect of any experiment. The organization of data is equally important so that appropriate conclusions can be drawn. (Siddharta Kalla, 2009) 1. Frequency and Percentage Distribution A frequency and percentage distribution is a display of data that specifies the percentage of observations that exist for each data point or grouping of data points. The process of creating frequency and percentage distribution involves identifying the total number of observations to be presented and counting the total number of observations within each data point or grouping of data points. FORMULA: Where: P = percentage F = frequency N = number of respondent 100x N f P 
  • 2. 2. Weighted Mean A weighted mean is a kind of average. Instead of each data point contributing equally to the final mean, some data points contribute more weight than others. (Andale, 2014) Formula: x̅ = ∑[( 𝑓)( 𝑤)] 𝑛 Where: x̅ = weighted mean F = frequencies to the given W = weights n =total number of respondents