SPSS or statistical package for social science is a software wrap up used for statistical investigation and data analysis involved in all the research methodologies of the dissertation. SPSS has a wide role in the dissertation, it assists in finding missing data’s from the list of numbers, their acquisition and interpretation and at last analyzing data result.
All the above process are equally important, but the most imperative among all is finding missing data. As, if a single number or a group of numbers is missing from the list of numbers it can misconstrue the entire study. Therefore, let’s do a deep study of how SPSS helps in finding missing data –
• Adding and finding average of all the numbers in the series – SPSS has a quality of adding a series of data and finding the average of the same. The series also includes the missing numbers and tells about the missing quantity. For an instance-
1) Average marks of 6 PhD students = M1+M2+ M3+ M4+M5+M6/6
2) The mean of the marks obtained by 6 PhD students = Mean ( A1, B2, C3, D4, E5, F6)
Average marks of 6 students cannot be calculated if any of them is missing whereas mean is easy to be intended. Missing numbers can be analyzed from the main series if the series has a minimum of 4 numbers in it.
Find out how many numbers are present (let’s say 4) and write in the way as –: MEAN. 4(A1, B2, C3, D4, E5, F6)
• Missing numbers Vs non missing numbers –
a. Both the missing and non missing numbers are compared first.
b. “Frequency Command” is used to compare the missing and non missing numbers along with other variables.
• Distribution of missing numbers –
a. “Aggregate” command is used by SPSS to find out the frequency and hence the missing numbers from the series.
Thus, this statistical package is useful in finding out the missing numbers.
Category: SPSS
The Combination SPSS with R-Language Can Do Wonder
The R language is used to develop statistical software which has become very popular with statisticians and data miners. R-language is extensively used for advanced data analysis. It provides a broad array of statistical and graphical practices such as:
• Classical statistical tests
• Time-series analysis
• Linear and nonlinear modeling
• Classification
• Clustering
It is an intelligent idea to combine SPSS software and R-syntax. It will benefit a lot. If you are not convinced, we have listed seven truly good reasons why you should use SPSS and R-language. Please have a look.
1. The interface is quite simple.
The SPSS graphical user interface supports a number of statistical analysis, data preparation, and analytical modeling algorithms.
2. There is no additional learning required.
SPSS software can easily handle statistical analysis, data, and modeling so you don’t have to learn any other thing.
3. Data preparation is easy.
SPSS software can read spreadsheets, text input, SAS files and more. It takes less time for extracting, manipulating and transforming data because wizards with pre-built connectors access data easily.
4. There are more options for output.
There is a one click accesses to SPSS presentation-ready charts and graphs. You can publish results to Word, PDF, PowerPoint, Excel and other formats. These results can be viewed on number of platforms.
5. The performance is superior.
The combination of SPSS with R-language works best for different environments such as SAP, Netezza Hana, and Oracle.
6. Group effort.
When you use SPSS software and R-syntax, you will lose the “lone work” aspect of R. With custom dialogs, you can generate new functions that anyone can use.
7. Security.
SPSS software provides an intelligent structure for securing, centralizing, and automating your analytical assets so that you can get assured that your environment is not at risk.
Combining the strengths of R with SPSS software makes logical sense.
SPSS & STATA – Effective Data Analysis Tools!
To reach a conclusion in a research program, a scholar has to go analyze and work with heavy sets of data. There are many data analysis tools, available at research centers, universities and colleges that help researchers during their task. SPSS and STATA are two among tens of others important data analysis tools.
SPSS – Statistical Package for the Social Sciences
It is a popular software application, designed by SPSS Inc., and owned by IBM. The IBM SPSS Statistics is not only a helpful tool for social science, but also for financial markets, health, medical, and various others areas or subjects. It is such a handy tool that even a non-researcher can analyze his/her pieces of data in this program. One can efficiently perform statistical analysis, data management, case selection, reshaping of file, derive data, and the documentation of data, cross tabulation, linear regression, factor analysis, with the user-friendly SPSS application.
STATA
Transfigured with the words Statistics and Data, STATA is a very useful tool for researchers. Produced by the StataCorp in the year 1985, the application is employed for data management, data analysis, statistical analysis, linear and multiple regression analysis, and graphic simulation in the research of economics, political science, biomedical, and social science. However, it has some limitations, as it opens only one dataset at one point of time; it stores its data and results in its virtual memory, as a result, it slows down, when analyzing large sets of data.
Conversely, many data analysts and frequent researchers find these tools unnecessary. Many of them assert and support using commonplace spreadsheet application, as MS Excel. Sometimes, the results and data released by these applications can complex and confusing. These programs are based on spreadsheet applications. And, if you have proficiency in Excel program, then you do not need to go with these tools.
Getting SPSS Help for Dissertation
SPSS refers to Statistical Package for Social Sciences, which is used while writing in academic papers, especially about on science topics. It is a technique used to analyze statistical data collected from various research sources. The technique also helps in analyzing descriptive as well as inferential statistics, which are commonly seen in a research for the dissertation. However, the authors are not proficient in using this analytical method due to which help becomes indispensable. Luckily, there are several resources that can help you understand and implement SPSS.
The very first source of help is the author’s dissertation committee whose primary objective is to help with writing dissertation. Therefore, you should not hesitate in taking their help for SPSS, especially for clearing your doubts and getting an insight about the use of this technique. It may happen that the committee members may appoint someone for assistance, as they are bound to help you.
Another source of help is the specific department in your school that might be conducting classes on SPSS and other dissertation techniques. Apart from that, you may also gain access to its instructional publications on SPSS. You can even seek help from technology help desk that every institution of higher learning offers. Herein, experts can guide you on one-to-one basis, free of charge.
A quick peek into Descriptive Statistics
After data collection, it is the data analysis task which needs to be undertaken in a brilliant manner. It is this task which decides the actual worth of a dissertation. By gathering timely assistance offered by a trained statistician, one can easily undertake the task of data analysis in a highly professional and effective manner.
Descriptive analysis is the process of analyzing data that helps in describing, representing and summarizing data in a meaningful manner. This process allows you to make conclusions beyond the data that has been analyzed. To put it more simply, descriptive analysis allows you to present the collected data in a much more meaningful manner so as to facilitate simpler interpretation of data. You may describe the central position of a frequency distribution for a group of data collected as per the research topic. You can easily describe this central position using a number of statistics, including the mode, median and mean. By using the descriptive statistics method, you can easily summarize large groups of data using a combination of tabulated description (i.e. tables), graphical description (i.e. graphs and charts) and statistical commentary (i.e. a detailed discussion of the results).
A very interesting video is here http://www.youtube.com/watch?v=5UXw-LlML-g which will provide you a quick guide on descriptive statistics. Hope this post of mine would have surely assisted you in gathering good amount of information on descriptive analysis of data.