Reliable SPSS Help for Your Thesis & Coursework
Navigate SPSS with confidence. From data entry and descriptive statistics to regression analysis and APA-formatted reports, we provide step-by-step help for your research.
Our Comprehensive SPSS Services
We support both the menu-driven and syntax-based approaches to SPSS, ensuring your analysis is accurate, well-documented, and easy to understand.
Data Entry & Setup
We help you correctly set up your .sav file, including defining variables in the Variable View, entering data, and handling missing values.Statistical Testing
Assistance with running and interpreting the most common statistical tests in the social sciences, including t-tests, ANOVA, chi-squared, and correlations.Advanced Modeling
Guidance on performing regression, factor analysis, and other multivariate procedures for your thesis or dissertation research.Output Interpretation & Syntax
We help you understand your SPSS output tables and can provide commented SPSS syntax (.sps) files for replicability.
What We Can Help You With: A Detailed Breakdown
Our SPSS support is perfect for students in psychology, sociology, education, marketing, and other social sciences.
Data Management and Preparation
Variable Setup: Correctly defining variable names, types, widths, decimals, labels, and values in the “Variable View.”
Data Entry: Manual data entry or importing from Excel and CSV files.
Data Transformation: Using Compute Variable to create new variables, Recode into Same/Different Variables, and Count Values within Cases.
Data Filtering: Using Select Cases to analyze subsets of your data.
File Manipulation: Merging files (adding cases or variables) and splitting files.
Descriptive Statistics and Graphing
Frequencies and Descriptives: Generating frequency tables, histograms, and summary statistics (mean, median, standard deviation).
Crosstabs: Creating contingency tables and running Chi-Squared tests of independence.
Chart Builder: Creating bar charts, scatter plots, and box plots using the SPSS Chart Builder.
Inferential Statistics and Hypothesis Testing
Compare Means: Independent-Samples T-Tests, Paired-Samples T-Tests, and One-Way/Two-Way ANOVA.
Correlations: Bivariate correlations (Pearson, Spearman) and partial correlations.
Non-parametric Tests: Mann-Whitney U, Wilcoxon signed-rank, Kruskal-Wallis tests.
Reliability Analysis: Calculating Cronbach’s Alpha to test for scale reliability.
Advanced Modeling and Multivariate Analysis
Regression: Linear Regression (including checking assumptions), Binary Logistic Regression, and Multinomial Logistic Regression.
Factor Analysis: Exploratory Factor Analysis (EFA) for survey development and validation.
MANOVA: Multivariate Analysis of Variance.
Cluster Analysis: Hierarchical and K-Means Cluster Analysis.
Output and Syntax
Interpreting Output: Explaining all parts of the SPSS output viewer, from the F-statistic in ANOVA to the Exp(B) in logistic regression.
APA Formatting: Helping you report your results in APA style.
SPSS Syntax: Writing, commenting, and debugging .sps syntax files to ensure your analysis is replicable.