What is it? Statistical analysis is the science of examining raw data and uncovering patterns and trends. Statistical analysis helps researchers and businesses identify new opportunities and make better business decisions. There are two main statistical techniques for data analysis: descriptive statistics and inferential statistics. Descriptive statistics describe the nature of data to be analyzed. This type of statistics presents raw data and simply shows what it is, but it does not allow for making conclusions. Inferential statistics studies the relationships between variables and draws a conclusion from the data; this type of statistics is a more complicated mathematical calculation.

There are numerous statistical methods, such as simple univariate analyses, multivariate analyses, factor analysis, cluster analysis, various types of regressions, hierarchical models, structural equation modeling, meta-analyses, and more. Choosing an appropriate statistical analysis is more important than selecting the fanciest and complicated statistical analysis.

If you are unsure what the best analyses should be used, let our consultants help you.

How can we help you?

• Evaluate and select the appropriate statistical methods
• Describe sample characteristics using frequency and descriptive statistics
• Explore the relationships of the data
• Create basic statistical analyses, including t test, univariate ANOVA, correlation, and chi-square
• Create advanced statistical analyses, including regression, multi-variate analysis, and multi-level modeling
• Perform longitudinal analyses, including repeated measures ANOVA/MANOVA, survival analysis, and time series
• Perform factor analysis, reliability, and cluster analysis
• Conduct nonparametric analyses
• Evaluate intervention effects (RCT)