Statistical Analysis

Written by Scott Martin
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Statistical analysis is useful not only in drawing conclusions from existing data, but also from drawing inferences and probable predictions in uncertain situations. There are many different type of statistical analysis depending on what type of data you are working with. However, selecting the most appropriate analysis and test can sometimes be confusing.

For basic questionnaire-based data collection, you might want to create a simple form to be filled out by study participants. For some people, the only analysis you need may be frequencies, averages, and distributions. Moreover, you might need to know what variables are correlated and which results are statistically significant.

Using ANOVA for Statistical Analysis

Analysis of variance, also known as ANOVA, draws comparison among two or more samples by analyzing their means. In order for this analysis to be used, several conditions must be met. First, independent data points are needed, and distributions must be considered to be normal. Secondly, a random population sample must be taken, without bias. Finally, make certain that your sample sizes are as similar as they can be.

Determining what data to collect, what statistical analysis to conduct, and how to interpret the results can be overwhelming. Many times, individuals do not have the time or expertise to answer these questions on their own. Often, a statistical consultant can save you time and money by helping you with study design, statistical analysis, and data interpretation.


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