Statistics using SPSS Assignment Help
SPSS is one of the most comprehensive and flexible tool for statistical analysis and data management. SPSS has range of applications in Statistics such as Descriptive Statistics, Hypothesis Testing, Regression Analysis, Factor Analysis etc.
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Following is the list of comprehensive topics in which we offer the quality solutions:
 Analysis of covariance
 Canonical Correlation Analysis
 Chisquare tests
 Correlation
 Discriminant Function Analysis
 Factor analysis
 Friedman Test
 Hierarchical multiple regression
 Independentsamples ttest
 KruskalWallis Test
 Logistic regression
 MannWhitney U Test
 Mixed betweenwithin subjects analysis of variance
 Multinomial Logistic Regression
 Multiple regression
 Multivariate analysis of variance
 Negative Binomial Regression
 Nonparametric statistics
 Oneway analysis of variance
 Oneway MANOVA
 Ordinal Logistic Regression
 Pairedsamples ttest
 Partial correlation
 Planned comparisons/Posthoc analyses
 Poisson Regression
 Preliminary analyses
 Probit Regression
 Spearman’s Rank Order Correlation
 Standard multiple regression
 Summary of techniques covered in this chapter
 Ttests
 Twoway betweengroups ANOVA
 Type 1 error, Type 2 error and power
 Wilcoxon Signed Rank Test
 Advanced Quantitative Methods
 Advanced Topics in State Space Models and Dynamic Factor Analysis
 Analysis of Variance
 Applied Econometrics
 ChiSquared Tests of Association
 Correlation
 Cross Sectional & Panel Data
 Data Management and Analysis for Monitoring and Evaluation in Development
 Data Management, Analysis, and Graphics
 Data Management, Regression, Panel Data Analysis & Research Output using Stata
 Dynamic Factor Models and Time Series Analysis in Stata
 Facts and Formulae Leaflets
 Frequency Tables and Contingency Tables
 Linear and logistic regression models
 Time Series Analysis
 Logistic Regression Models: Modelling binary, proportional and categorical response models
 Longitudinal Data Analysis
 Management, Analysis and Graphics of Epidemiology Data
 Micro econometrics
 Modeling count data: Understanding and modeling risk and rates
 Multilevel & Longitudinal Modelling
 Multilevel Modeling
 Multivariate Methods
 Nonparametric Methods
 Panel Data Analysis
 Power and Sample Size
 Presenting and Summarizing Data
 Propensity Score Analysis
 Rates and survival analysis: Poisson, Cox, and parametric survival models
 Regression and Model Building
 Regression Models for Categorical Dependent Variables using Stata
 Sample Size and Statistical Power
 Stata programming





