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What are the steps to calculate p-value?
Example: Calculating the p-value from a t-test by hand
- Step 1: State the null and alternative hypotheses.
- Step 2: Find the test statistic.
- Step 3: Find the p-value for the test statistic. To find the p-value by hand, we need to use the t-Distribution table with n-1 degrees of freedom.
- Step 4: Draw a conclusion.
What is the formula for p-value in Excel?
As said, when testing a hypothesis in statistics, the p-value can help determine support for or against a claim by quantifying the evidence. The Excel formula we’ll be using to calculate the p-value is: =tdist(x,deg_freedom,tails)
When to use correlation and p-value in feature selection?
Feature selection — Correlation and P-value. Often when we get a dataset, we might find a plethora of features in the dataset. All of the features we find in the dataset might not be useful in building a machine learning model to make the necessary prediction. Using some of the features might even make the predictions worse.
How does removing a feature affect the p-value?
Removal of different features from the dataset will have different effects on the p-value for the dataset. We can remove different features and measure the p-value in each case. These measured p-values can be used to decide whether to keep a feature or not.
Which is the best method to calculate p-values?
This is probably a simple question but I am trying to calculate the p-values for my features either using classifiers for a classification problem or regressors for regression. Could someone suggest what is the best method for each case and provide sample code?
What does it mean to have a small p value?
A very small p-value, which is lesser than the level of significance, indicates that you reject the null hypothesis. P-value, which is greater than the level of significance, indicates that we fail to reject the null hypothesis. The formula for the calculation of the p-value can be derived by using the following steps: How to Provide Attribution?