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Chapter 12
Statistical applications
to construction
12.1 Section introduction
Statistics is a body of methods enabling us to draw reasonable conclusions from
data. Statistics is divided into two general types, descriptive statistics and sta-
tistical inference. With descriptive statistics, we summarize data and make cal-
culations and tables or graphs that can be comprehended easily. Statistical
inference involves drawing conclusions from the data. In this section, we con-
sider practical ways to enhance man-hour analysis by graphic and analytic tech-
niques. Statistical methods and indexing are considered with the intention to
point out the connection to construction. This section provides the reader the
knowledge to use construction statistics to collect, analyze, forecast, and use
learning curves and time series to validate data and prepare detailed accurate
estimates and bid proposals. The section includes practical examples of statis-
tical applications and methods to help the reader understand the importance of
man-hour analysis and estimating. To get the most benefits from the statistical
applications, the reader should understand exponents, logarithms, and simple
algebraic manipulations. It also helps, but is not required, to understand regres-
sion analysis. Readers can enter data into the Excel spreadsheets to get the
results they need.
Foreman’s report and man-hour analysis
Consider an example for the field installation of an air-cooled condenser. Data
are collected in the field for the condensate headers. The foreman reports the
descriptions of the task, elapsed time, and man-hours completed. The data
are examined for consistency, completeness, and accuracy. The report is then
compiled for analysis to verify the historical data.
12.2 Analysis of Foreman’s report
See Tables 12.2.1 and 12.2.2.
Industrial Process Plant Construction Estimating and Man-Hour Analysis.
https://doi.org/10.1016/B978-0-12-818648-0.00012-0
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