Data Analysis In Management With Spss Software by J.P. VermaData Analysis In Management With Spss Software by J.P. Verma

Data Analysis In Management With Spss Software

byJ.P. Verma

Paperback | January 29, 2015

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This book provides readers with a greater understanding of a variety of statistical techniques along with the procedure to use the most popular statistical software package SPSS. It strengthens the intuitive understanding of the material, thereby increasing the ability to successfully analyze data in the future. The book provides more control in the analysis of data so that readers can apply the techniques to a broader spectrum of research problems. This book focuses on providing readers with the knowledge and skills needed to carry out research in management, humanities, social and behavioural sciences by using SPSS.
Dr. J.P.Verma is a professor of statistics at the Lakshmibai National University of Physical Education, Gwalior and has experience of more than three decades of teaching applied statistics to the students of different disciplines. Professor Verma possesses three masters degree in statistics, psychology and computer application besides ...
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Title:Data Analysis In Management With Spss SoftwareFormat:PaperbackDimensions:482 pages, 23.5 × 15.5 × 1.73 inPublished:January 29, 2015Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:8132217101

ISBN - 13:9788132217107

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Table of Contents

Chapter 1: Data Management.-Chapter 2 : Descriptive Analysis.-Chapter 3 : Chi-Square test and its Application.-Chapter 4 : Correlation Matrix and Partial Correlation - Explaining Relationships.-Chapter 5 : Regression Analysis and Multiple Correlations - For Estimating a Measurable Phenomenon.-Chapter 6 : Hypothesis testing for decision making.-Chapter 7 : One Way ANOVA - For testing the variability among group Means.-Chapter 8 : Two Way Analysis of Variance - For Understanding the Causes of Variations.-Chapter 9 : Analysis of Covariance- To study the role of covariate in Experimental Research.-Chapter 10 : Cluster Analysis- For segmenting the population.-Chapter 11 : Application of Factor Analysis - To study the Factor Structure among Variables.-Chapter 12 : Application of Discriminant Analysis - For developing a classification model.-Chapter 13 : Logistic Regression - Developing a model for Risk Analysis.-Chapter 14 : Multidimensional Scaling for product positioning.