There are 15 tools you can use:
ANOVA (Analysis of Variance) is a variance tool to develop and confirm an explanation for the observed data.
There are 3 types of Anova:
- Two-Factor With Replication
- Two-Factor Without Replication
The correlation analysis tool provides an output table and a matrix to know whether 2 variables tend to move together.
Covariance is usually used in tandem with the correlation analysis tool especially when you have lots of different measurement variables on a set.
4. Descriptive Statistics
This tool provides information and data about the central tendency and variability of your data.
5. Exponential Smoothing
The Exponential Smoothing tool smooths time-series data through an exponential window function.
6. F-Test Two-Sample for Variances
This tool tests the null hypothesis that the samples from two distributions are equal variances.
7. Fourier Analysis
The Fourier Analysis tool breaks down a harmonic series into its most basic components using sinusoidal functions and analyzes the periodic data.
A Histogram represents the distribution of numerical data.
9. Moving Average
This is a technical analysis tool usually used in sales which constantly updates the average price. It works by unmasking the noise brought about by random short-term fluctuations.
10. Random Number Generation
The Random Number Generation analysis tool lets you generate random numbers with respect to a number of variables and other options.
11. Rank and Percentile
This tool outputs a table with the ordinal and percentage rank the values in a data set.
This is a linear regression analysis tool that analyzes the effect of different variables on a single dependent variable.
The Sampling tool is useful in performing an analysis of a smaller sample of your data and look for variations. It treats the input range (the sample) as a population.
The t-Test tool tests the equality of the population means in a sample.
There are three types of t-Test:
- Paired Two Sample For Means
- Two-Sample Assuming Equal Variances
- Two-Sample Assuming Unequal Variances
15. z-Test: Two Sample for Means
This statistical tool is useful in testing the null hypothesis that the population means of two populations are different considering the variances are known the sample size is big.