Question

Why are conditional test procedures an integral part of statistics? Provide a real world example using pseudocode.

Answer 1

In order to understand the impact of the conditional test process in statistics we should first of all understand as to what is a conditional test procedure in statistical analytics.

A conditional test procedure is defined as a process that tries to estimate the significence of the impact of the given condition/treatment/experiment/xercise of the given samples. This highlights the impact (or no impact) of the condition on the sample under treatment. Some of the examples of conditional test are fischer test.

A real life example of conditional test can be to understand the impact/significence of a strict statistics teacher on the overall performance of students of class 8th in statistics .Here in the conditional test procedure we will build a hypothesis model and ascertain a test statistics. Based on the vlaue of test statistic ,we can conclude if the performance of the students have improved because of strict teacher or not.

The conditional test procedure has following siginficence

1. Tells us if the exposed samples are exachangeble in null hypothesis or not.

2. Provides mathematical insight into a sample validity which appears impossible otherwise

3. Data stratification

4. Rationalization of data. No garbage .

In programming parlance this can be explained as follows.

1.When we write an algorithm for a conditional test ,what we essentially do is that we define the boundaries /conditions in a formal defined launguage to recall a function/value/output.

2. Starting from an initial condition/state/input values ,the series of commands describe a process/algorithm that when executed, proceeds through a finite number of well-defined successive states and eventually produce an output/result /. The alogorithm is programmed to terminate at tihs stage after providing final output after given nmber of iterations.