What-if analysis is one of the main tools used in Excel for decision making. Basically, it consists of testing one or more hypotheses about a set of data in order to determine whether they are true or false.
There are different types of hypothesis analysis, but one of the most common is the t-test. This test is used to compare the mean of two data samples and determine whether they are statistically different from each other.
To perform a t-test in Excel, you need to take two samples of data and calculate the mean, standard deviation, and sample size for each of them. You can then use the T.TEST function to calculate the t-test value and determine whether the means are statistically different.
Another widely used hypothesis analysis is the chi-square test. This test is used to determine whether there is a relationship between two categorical variables. For example, you can use the chi-square test to determine whether there is a relationship between age and consumption of a particular product.
To perform a chi-square test in Excel, you need a table of observed frequencies and a table of expected frequencies. The table of observed frequencies contains the actual data, while the table of expected frequencies contains the data that would be expected if there were no relationship between the variables.
In addition to these two examples, there are many more what-if analyzes that can be performed in Excel. Some of these include the F test, the Z test, the Wilcoxon test, among others.
In summary, what-if analysis is a fundamental tool for data-driven decision-making. With it, it is possible to test different hypotheses and determine whether they are true or false, which can help guide future actions and strategies.
