Basic engineering data collection and analysis / Stephen B. Vardeman, J. Marcus Jobe.

Abridgment and modernization of: Statistics for engineering problem solving. 1994.

Engineering Statistics: What and Why --
Basic Terminology --
Types of Statistical Studies --
Types of Data --
Types of Data Structures --
Measurement: Its Importance and Difficulty --
Mathematical Models, Reality, and Data Analysis --
Data Collection --
General Principles in the Collection of Engineering Data --
Measurement --
Sampling --
Recording --
Sampling in Enumerative Studies --
Principles for Effective Experimentation --
Taxonomy of Variables --
Handling Extraneous Variables --
Comparative Study --
Replication --
Allocation of Resources --
Some Common Experimental Plans --
Completely Randomized Experiments --
Randomized Complete Block Experiments --
Incomplete Block Experiments (Optional) --
Preparing to Collect Engineering Data --
A Series of Steps to Follow --
Physical Preparation --
Elementary Descriptive Statistics --
Elementary Graphical and Tabular Treatment of Quantitative Data --
Dot Diagrams and Stem-and-Leaf Plots --
Frequency Tables and Histograms --
Scatterplots and Run Charts --
Quantiles and Related Graphical Tools --
Quantiles and Quantile Plots --
Boxplots --
Q-Q Plots and Comparing Distributional Shapes --
Standard Numerical Summary Measures --
Measures of Location --
Measures of Spread --
Statistics and Parameters --
Plots of Summary Statistics --
Summary Statistics and Personal Computer Software --
Descriptive Statistics for Qualitative and Count Data (Optional) --
Numerical Summarization of Qualitative and Count Data --
Bar Charts and Plots for Qualitative and Count Data.

"In Basic Engineering Data Collection and Analysis, Stephen B. Vardeman and J. Marcus Jobe stress the practical over the theoretical. Step by step, students get real engineering data and scenario examples along with chapter-long case studies that illustrate concepts in realistic, thoroughly detailed situations. This approach encourages students to work through the statistics by carrying data collection and analysis projects from problem formulation through preparation of professional technical reports - just as if they were on the job."--Jacket.