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Statistics - Social Sciences & Law | Data Analysis in Management with SPSS Software

Data Analysis in Management with SPSS Software

Verma, J.P.

2013, XXI, 481 p. 178 illus.

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  • A self learning text for the use of SPSS software in data analysis
  • It helps in understanding the application of advanced statistical techniques by using SPSS and interpreting the findings
  • Simple approach to learn the use of statistics (including multivariate analysis) in management and other areas of learning

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.

Content Level » Upper undergraduate

Keywords » Cluster Analysis - Factor Analysis - Logistic Regression - Multivariate Analysis - SPSS

Related subjects » Business, Economics & Finance - Social Sciences & Law

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.

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