13 Statistical Analysis Methods for Data Analysts & Data Scientists

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Statistical analysis techniques encompass a wide range of methods used to analyze data, make inferences, and draw conclusions about populations or datasets. Here is a list of various statistical analysis techniques:

1. Descriptive Statistics:

These techniques provide a summary of data, including measures of central tendency (mean, median, mode), variability (range, variance, standard deviation), and the shape of data distributions.

• Measures of central tendency (mean, median, mode)
• Measures of variability (range, variance, standard deviation)
• Measures of distribution (skewness, kurtosis)
• Frequency distributions and histograms

2. Inferential Statistics:

These methods are used to draw conclusions about populations or datasets based on a sample. They include hypothesis testing, confidence intervals, regression analysis, correlation analysis, and more.

a. Hypothesis Testing:

• Student’s t-test: A statistical test used to determine if there is a significant difference between the means of two groups. It’s commonly employed when working with small sample sizes.