Statistical Technology Introduction

Microsoft Excel

As managers, you all are already very familiar with Excel. This is a ubiquitous and quite powerful tool for everyday analysis. We can use this tool to quickly create charts, graphs, and even run basic statistical analysis. Excel has quite an extensive library of functions. Also, the Data Analysis Toolpak along with the PHSTAT plug-in (please refer to the course syllabus on how to purchase) will allow us to perform the many analyses we will learn in this course.

Despite the ubiquity and ease of use, Excel falls short in a few areas. It can’t handle very large sets of data, there was no concept of using variables and variable types (we will learn about these in Lesson 1), and it does not handle categorical data (e.g., gender, answers in a multiple-choice survey) well. You may refer to

Why you must stop reporting data in Excel and The risk of using spreadsheets for statistical analysis for more on this topic.

Excel Resources

• Goodwill Community Foundation's Excel 2016 Tutorial: The tutorial covers from basic to somewhat advanced.
• Microsoft Excel Video Tutorials

IBM SPSS

Originally termed Statistical Package for the Social Sciences (SPSS), SPSS was acquired by IBM in 2009 and is now termed as IBM SPSS Statistics. This is a widely-used statistical tool used in social sciences as well as in marketing, healthcare, government, and other fields. The main advantages of SPSS over Excel (or any typical spreadsheet) are:

• The concept of cases and variables is built into it: On its surface, SPSS looks a lot like a typical spreadsheet application. The rows in SPSS represent cases (e.g., survey respondents); and the columns represent variables observed from those cases (e.g., salary, age of the respondents). Because of this case/variable arrangement, it makes calculations easy by using the variable name (e.g., select only the respondents whose age < 30). This is particularly advantageous when dealing with large sets of data.
• Various statistical tests (ANOVA, chi-square test, regression) are easily available with much more rigorous options: Instead of having to select an entire range of data in Excel (this becomes particularly cumbersome with large data sets), you choose the variable name in SPSS and mention the test you want to perform. The output appears in a different window with all relevant information (as opposed to in a new cell in Excel). This is very useful, especially while handling large amounts of data as it keeps the raw data separate from any output.
• Easier coding of data: A lot of today’s data, especially survey data, is numerically coded. For example, a response of “strongly agree” might become a 6; a level of education such as “completed high school” or “some college” might become a 1 or 2. SPSS makes it possible to automatically define the variable so that its coded values are keyed to their original meanings. As we will see later, this makes data analysis and making charts and graphs much simpler.

SPSS Resources

• SPSS beginner’s tutorial from SPSS Tutorials.com
• SPSS tutorial from Statistics How To