statistics | Lean Six Sigma, Six Sigma Certification

There are several statistics that are important for business analysis, including:

Descriptive statistics: Descriptive statistics are used to summarize and describe important features of a data set. They can include measures such as mean, median, mode, range, standard deviation, and variance.

Inferential statistics: Inferential statistics are used to draw conclusions about a population based on a sample of data. They can include hypothesis testing, confidence intervals, and regression analysis.

Time series analysis: Time series analysis is used to analyze data over time, such as sales data or financial data. This can include techniques such as trend analysis, seasonal analysis, and forecasting.

Correlation analysis: Correlation analysis is used to examine the relationship between two variables. This can include measures such as Pearson’s correlation coefficient and Spearman’s rank correlation coefficient.

Statistical modeling: Statistical modeling is used to create models that can help explain and predict business outcomes. This can include techniques such as linear regression, logistic regression, and decision trees.

Overall, the specific statistics that are needed for business analysis will depend on the specific question being asked and the data that is available.


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