SPSS is a statistical analysis program, commonly used in Research, whether it be in the field of Social Sciences, Marketing, Operations, or any other field where it is desirable to extract meaningful connections from large sets of data.
SPSS was initially developed for use in the Social Sciences, as evident in the name – Statistical Package for the Social Sciences. (Source: http://en.wikipedia.org/wiki/SPSS)
Day 1 of the classes focused on a basic introduction to SPSS and some of its data-crunching capabilities.
Interface: The interface consists of a spreadsheet-like screen (GUI similar to Excel), which is used for entry of data, and an Output Screen (CLI/GUI), in a separate window.
There are 2 tabs at the bottom, named Data View and Variable View – to enter data. All outputs in terms of calculations and analyses performed on this data are shown in the Output Window.
Data Entry: Data type, along with Name of variable, length, labels, measurement type, etc. is defined in the Variable View, whereas actual entries of respondents, as entered by the Analyst, are visible in the Data View. An instance of a variable, i.e., an actual entry, is called a Case.
Data Analysis: Once basic data definition and entry are complete, the Analyst is ready to use the capabilities available at his disposal, thanks to SPSS, to crunch this data.
Some tools available in SPSS are a set of descriptive statistical tools, called Cross Tabs.
Cross tabs allow a researcher to check the dependence between any two variables.
Examples: An example for this was illustrated, using a General Social Survey (With 67 variable types), built into SPSS. The sample was from a Social Survey conducted in the US, and contained respondents answers to such questions as Age, Gender, Race, Education Levels, Personal Life, Income, Political Views, Music tastes etc.
The Hypothesis tested was that people who get married below a particular age (as indicated by Age of First Marriage) have lower education levels, and the corollary of the same is that people with higher education levels get married later in life.
The data was categorized based on education level of individual respondents, as well as when they first got married. A chi-square analysis was conducted on this data, and since the confidence level (indicated by a score of .005 or more) was above 95%, it was accepted.
Hence, people with lower education levels had their first marriage earlier.
Similarly, a Retail Satisfaction Survey (With 18 Variable Types, ranging from Age, Gender, Payment methods, to satisfaction levels) was also analyzed, wherein data indicated that the general satisfaction level of shoppers who visited the Clothing Dept. in a Store (Store 2 of 4)of a Retail chain, who were attended to by staff , was actually lower than those who were not attended to.
It followed that most of these shoppers were also dissatisfied in the Shoe and Stationery Depts. Indicating they were women. This was corroborated by incidental data collected by the store (Age, Gender etc., apart from Satisfaction Level Indicators).
The second data set, i.e., that of the retail satisfaction survey, exposed us to the concept of spurious data. The data may look alright, even when subjected to rigorous statistical analysis. However, it is up to the researcher to use his experience as well, to ensure that the inferences are not erroneous in nature.
Conclusion: SPSS is very powerful statistical software, with a large number of mathematical and statistical functions, which places significant data analysis capabilities in the hands of the present-day researcher. A simple peek into the software on Day 1 was sufficient to convince me about the relevance and power of this software.
As a student of Marketing, as well as a future Marketer, I am left with no doubt that this tool will provide me with significant insights into the minds of the consumer. Any manager must have rudimentary knowledge of this program.
A word of caution: However, this tool is only as good as the User, and it is ultimately up to the experience and skill of the Manager to decide whether or not to risk his scarce resources on the results of a Computer Program alone.
Remember, torture numbers and they will confess to anything.
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Abhishek Nair,
Roll Number 12063,
Marketing Batch of 2009-11,
SIBM Bangalore.
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