Are you looking for high-quality data analysis/data mining services for your project? Look no further! This service has been designed to solve your problems regarding the statistical analysis of quantitative and qualitative data with a detailed report using various software: SPSS, Python, R, Xlstat, Jamovi, Gretl, GraphPad, SPSS Amos, SmartPLS...
With over 14 years of experience as a statistician and data analyst, I possess a wealth of knowledge in various statistical methods and their practical applications. I take pride in offering unparalleled data analysis services tailored to meet your needs, whether you require assistance with doctoral research or business-related projects. My expertise spans across diverse fields, including economics, marketing, medicine and epidemiology, psychology, sociology, chemistry, and more.
As a seasoned professional, I can provide invaluable support throughout the research process. From designing robust studies to collecting and cleaning data, I ensure that the foundation of your analysis is solid. Utilizing my deep understanding of statistical techniques, such as regression analysis, hypothesis testing, ANOVA, clustering, factor analysis, and others, I employ the most suitable methodologies to analyze your data effectively.
My services extend beyond statistical analysis; I am proficient in interpreting results and presenting them in a clear and meaningful manner. Whether you require comprehensive reports, visualizations, or presentations, I can deliver outputs that elucidate the key findings of your research.
By leveraging my extensive experience and expertise, you can trust me to deliver accurate and insightful data analysis, helping you gain a deeper understanding of your research questions and empowering you to make informed decisions.
I also have the recipe to make your research work easier by analyzing your research data using statistical methods that adapt to your data with a comprehensive and unbiased analysis report. Here are some of my skills and competencies:
Outlier detection and data cleaning
Construction of any type of graph
Descriptive analysis (frequency tables, graphs...)
Correlation analysis (Pearson, Spearman, Kendall's Tau...)
Association or dependency analysis (Chi-square test, McNemar...)
Comparison of 2 means (t-test, Mann Whitney, Wilcoxon...)
Comparison of multiple means (ANOVA, Kruskal-Wallis, Friedman...)
Regression (simple linear, multiple, logistic...) and its GLM (generalized linear models) extensions
Structural equation modeling
Analysis of variance (one-factor, two-factor, repeated measures...)
Factor analysis (PCA, CFA, CAM...)
Classification methods (hierarchical clustering, AFD...) and clustering (k-means...)
Study and validation of measurement scales (validity, reliability, Cronbach's alpha...)
Experimental design (full, Box-Behnken...) for process optimization
Machine learning (SVM, ANN...)
I offer the following options:
-Frequency tables and graphs (with fewer than 6 variables): Up to 6 frequency table and 6 graphs
-Parametric and/or non-parametric tests (up to 3 tests): ANOVA test, Student test, Mann Whitney test or Kruskal Wallis test.
-Simple or multiple linear regression (One model): Explain a dependent variable with one or more independents variables
-Correspondence analysis (One analysis) : explore relationships between two categorical variables and visually represent their associations in a low-dimensional space
-Principal component analysis (One analysis): Display explained variance ratios, scree plots, loadings, and biplots to interpret the relationships and contributions of variables in a reduced-dimensional space
-Multiple correspondence analysis (MCA) (One analysis): Analyze categorical data involving more than two variables, providing insights into the relationships and patterns among multiple categorical variables simultaneously
-Performing descriptive analysis of a database (up to 20 variables and unlimited observations): Summarizing and describing data through various statistical measures and visualizations to gain insights into its characteristics, such as central tendency, dispersion, and distribution
- Bivariate analysis with tests of association or correlation (up to 20 relationships): Examine the relationship between two variables in a dataset. It aims to understand the association, correlation, or dependence between the two variables and determine if there is a relationship or pattern between them.
FOR 5 EUROS, you will receive 2 graphs or two contingency tables of your choice from your database with an unlimited number of observations. Each graph or table will be interpreted in 2 sentences. Delivery will be made within one day (24 hours) in Word or PDF format.
Lastly, my priorities are customer satisfaction and timely delivery!