Statistical Thinking (eBook)

Improving Business Performance

Roger W. Hoerl, Ronald D. Snee (Autoren)

eBook Download: EPUB

2020 | 3. Auflage
John Wiley & Sons (Verlag)
978-1-119-60573-7 (ISBN)

Infos

Apply statistics in business to achieve performance improvement

Statistical Thinking: Improving Business Performance, 3rd Edition helps managers understand the role of statistics in implementing business improvements. It guides professionals who are learning statistics in order to improve performance in business and industry. It also helps graduate and undergraduate students understand the strategic value of data and statistics in arriving at real business solutions. Instruction in the book is based on principles of effective learning, established by educational and behavioral research.

The authors cover both practical examples and underlying theory, both the big picture and necessary details. Readers gain a conceptual understanding and the ability to perform actionable analyses. They are introduced to data skills to improve business processes, including collecting the appropriate data, identifying existing data limitations, and analyzing data graphically. The authors also provide an in-depth look at JMP software, including its purpose, capabilities, and techniques for use.

Updates to this edition include:

• A new chapter on data, assessing data pedigree (quality), and acquisition tools
• Discussion of the relationship between statistical thinking and data science
• Explanation of the proper role and interpretation of p-values (understanding of the dangers of 'p-hacking')
• Differentiation between practical and statistical significance
• Introduction of the emerging discipline of statistical engineering
• Explanation of the proper role of subject matter theory in order to identify causal relationships
• A holistic framework for variation that includes outliers, in addition to systematic and random variation
• Revised chapters based on significant teaching experience
• Content enhancements based on student input

This book helps readers understand the role of statistics in business before they embark on learning statistical techniques.

DR. ROGER W. HOERL is an associate professor at Union College where he teaches statistics, engineering statistics, design of experiments, regression analysis, and big data analytics. Previously, he led the Applied Statistics Laboratory at GE Global Research.

DR. RONALD D. SNEE is founder and president of Snee Associates, an authority on designing and implementing organizational improvement and cost-reduction solutions. Prior to this role, he worked at the DuPont Company in a variety of assignments. Snee has co-authored five books and published more than 330 articles on process improvement, quality, and statistics.

Textauszug

Introduction to JMP*

JMP is desktop data analysis software from SAS, the world's leading provider of analytics solutions for industry. JMP is easy to learn and use and contains a very broad collection of tools for data analysis and visualization. It also works well with data in other formats, including Microsoft Excel, and is available for both Windows and Macintosh operating systems. A free 30-day trial that you can easily download and install to use for the examples in this book is available at www.jmp.com/trial.

In this section we will introduce you to some of the essential functions of JMP, including basic navigation, how to import data, how to run basic analyses, and where to get help. You will find additional resources at www.jmp.com/learn and many excellent books at www.jmp.com/books.

WHY JMP?

In one package, JMP contains all the basic graphing and analysis tools found in spreadsheets as well as more advanced platforms for regression, design of experiments, and quality and predictive analytics. JMP is designed around the workflow of the data analyst and provides several important advantages to the user. The first of these is that JMP guides you to the appropriate analysis for your data. The results are always driven by the type of data you have and the general purpose of your analysis. JMP then provides contextual options, allowing you to dive deeper into the analysis.

The second advantage is that graphs nearly always accompany statistical results; the graphs are presented first, followed by the numerical results. Note that JMP also provides a separate Graph menu that contains additional visualization tools that are independent of numerical results. Another important advantage is that graphs in every platform are dynamically linked to the data, allowing one to explore relationships visually and to perform data management tasks on the fly. We are confident that JMP will save you time and yield better results.

JMP MENUS

At the top of the JMP window, you see a series of menus (File, Edit, Tables, etc.). These menus are used to open or import data, to edit or restructure data, to design an experiment and to create graphs and analyses. There is also a valuable source for assistance through the Help menu, which is discussed later. Note that while we are illustrating JMP on the Windows platform, Macintosh instructions are nearly identical. (See Figure A.)

FIGURE A JMP Menu Bar

The menus are organized in a logical sequence from left to right:

• File is where you go to open or import data and to save, print, or exit JMP. It is also where you can customize the appearance or settings within JMP through Preferences.
• Edit appears on the Mac home window and, on Windows, in individual data tables and reports (but not on the Windows Home window). Edit provides the usual cut, clear, copy, paste, and select functions, as well as undo, redo and special JMP functions.
• Tables provide the tools to manage, summarize, and structure your data.
• DOE contains the Design of Experiments tools and the sample size and power calculators.
• Analyze contains the analysis tools that generate both graphs and statistics. It serves as the home for all of JMP's statistical tools from the most basic to advanced.
• Graph contains graphical tools that are independent of statistics (at least initially). Graphs in this menu include basic charts to advanced multivariable and animated visualization tools.
• Tools allows you to transform your mouse into a help tool, a selection tool, a brushing tool or scrolling tool, and much more.
• View lets you view or hide windows or toolbars.
• Window helps you manage windows within JMP.
• Help provides resources for learning and using JMP. The Help menu provides access to the learning resources (including all of the documentation) that you will use as you expand your knowledge of JMP and its features and learn about statistics.

IMPORTING DATA

Importing data is similar to opening any file from a desktop application. In Windows, click File > Open to launch the Open dialog window. Near the bottom of the window you will notice a file type button that allows (see Figure B) you to select from a variety of data formats that JMP can read natively. If you know the format of your data, select that format to see available files of that type.

FIGURE B File > Open

Select or highlight the file and click Open (see Figure C).

FIGURE C JMP Import Formats

JMP can also import data extracted from databases via ODBC. For more information about these and other data importing functions, click Help > JMP Help>Using JMP.

THE JMP DATA TABLE

The JMP Data table is similar to any spreadsheet with a few important differences. JMP requires your data to be structured in a standard form, where variables are in columns and observations are in rows. Whether you are importing data from another source or creating a new data table, make sure this format is in place.

The data table also contains metadata or information about your data. The most important of these is the modeling type of your variables, which is displayed in the middle (Columns) panel on the left-hand side of the data table. The modeling type will drive the type of results you get from an analysis, meaning that JMP only produces statistics and graphs that are suitable for the type of data you are working with and the analysis at hand. You can change the modeling type to another appropriate alternative by simply clicking on the icon and selecting the desired modeling type. (See Figure D.)

FIGURE D JMP Data Table

THE ANALYZE MENU

As noted earlier, the Analyze menu is where you will find the statistical tools in JMP. Nearly all of the statistical results you generate in this menu will also generate an associated graph, and that graph will appear first. The menu is designed to support the objective of your analysis and provides a very logical sequence to the order in which the items appear. The most basic and general tools are at the top of the menu, and as you move down the menu, the tools become more advanced or specific.

JMP contains few menu items relative to its capabilities because the combination of your modeling type and analysis objective will always narrow down and produce the appropriate graphs and statistical results. Let us take a look at some of the items on the Analyze menu. In the top section, you find the following (see Figure E):

• Distribution (for univariate statistics). A good starting point with any data set. See what each column looks like and generate summary statistics. Confidence intervals and hypothesis tests for one variable (Chapter 9).
• Fit Y by X (for bivariate statistics). Explore relationships between any two variables (one Y and one X). Simple regression, one-way, contingency, and so forth (Chapter 7).
• Fit Model. A robust platform for multiple regression and general modeling (more than one Y or X) (Chapter 7).

FIGURE E JMP Analyze Menu

The next items (beginning with Modeling) are families of tools that contain submenus with more specific functions.

The Modeling menu contains platforms for data mining (Partition and Neural), time series forecasting, and categorical data analysis among others (see Figure F). The Multivariate Methods menu contains common multivariate tools, such as Clustering, Factor Analysis and Correlations. While these two menu items are beyond the scope of this book, the interested reader can find more information at Help > JMP Help>Multivariate Methods.

FIGURE F JMP Modeling Menu

The Quality and Process menu was recently added and has consolidated many of the quality-related tools in a logical manner. Control Chart Builder allows you to create control charts in a drag-and-drop manner and will be illustrated later (Figure G). More information is available at Help > JMP Help > Quality and Process Methods.

FIGURE G JMP Quality and Process Menu

JMP DIALOG WINDOWS

When you select most Analyze menu items, a dialog window will appear consisting of three main components (Figure H):

1. On the left side of the window, the Select Columns area contains the variables in your data table that you can select for your analysis.
2. In the middle section, the Roles in which you'd like to cast those variables (you can do this by dragging them into the role, or by selecting them and then clicking the button for that role).
3. On the right side are a series of Actions you can take. Click OK to launch the specified analysis.

FIGURE H JMP Dialog Window

THE GRAPH MENU

The graph menu contains a wide variety of data visualization platforms. Unlike the analyze menu where you generate both statistical results and graphs, the Graph menu generates only graphs of your data or models (at least initially) (Figure I).

...

Produkt-Details

• Erscheint lt. Verlag: 25.8.2020
• Reihe/Serie: SAS Institute Inc
• Reihe/Serie: SAS Institute Inc
• Reihe/Serie: Wiley and SAS Business Series
• Sprache: englisch
• Themenwelt: Wirtschaft ► Betriebswirtschaft / Management ► Unternehmensführung / Management
• Themenwelt: Wirtschaft ► Volkswirtschaftslehre ► Ökonometrie
• Schlagworte: Business & Management • Business Statistics • Business Statistics & Math • business statistics for students • data visualization and display • improving business processes • JMP software • statistical and graphical analysis • statistical business analysis • statistical engineering • Statistical Techniques • Statistics for industry • statistics for managers • strategic value of data • Wirtschaftsmathematik • Wirtschaftsmathematik u. -statistik • Wirtschaft u. Management
• ISBN-10: 1-119-60573-3 / 1119605733
• ISBN-13: 978-1-119-60573-7 / 9781119605737