What is testSetup and its purpose and how many we can have in a single test class?
You can have only one test setup method per test class. If a fatal error occurs during the execution of a test setup method, such as an exception that’s caused by a DML operation or an assertion failure, the entire test class fails, and no further tests in the class are executed.
What is the use of @isTest in Salesforce?
For Apex code saved using Salesforce API version 24.0 and later, use the @isTest(SeeAllData=true) annotation to grant test classes and individual test methods access to all data in the organization. The access includes pre-existing data that the test didn’t create.
What is the use of @TestVisible?
Use the TestVisible annotation to allow test methods to access private or protected members of another class outside the test class. These members include methods, member variables, and inner classes. This annotation enables a more permissive access level for running tests only.
What happens when you split a training and a test set?
We’d expect a lower precision on the test set, so we take another look at the data and discover that many of the examples in the test set are duplicates of examples in the training set (we neglected to scrub duplicate entries for the same spam email from our input database before splitting the data).
Why is an effect size important in independent t test?
Effect sizes are important because whilst the independent t-test tells you whether differences between group means are “real” (i.e., different in the population), it does not tell you the “size” of the difference. Providing an effect size in your results helps to overcome this limitation.
What is the purpose of a test set?
Assuming that your test set meets the preceding two conditions, your goal is to create a model that generalizes well to new data. Our test set serves as a proxy for new data.
Can a t test be used for more than two groups?
A t-test should not be used to measure differences among more than two groups, because the error structure for a t-test will underestimate the actual error when many groups are being compared. If you want to compare the means of several groups at once, it’s best to use another statistical test such as ANOVA or a post-hoc test.