Hypothesis testing, innocent until proven guilty

 Hypothesis testing is a way of using data and evidence to decide if a particular idea or theory is likely to be true. It involves making a guess or prediction (called a hypothesis) about what might be happening, and then collecting data and evidence to see if the prediction is supported. For example, if you have a hypothesis that a certain type of plant will grow faster in sunlight than in the shade, you can test this by setting up two groups of plants, exposing one group to sunlight and the other group to shade, and then measuring how fast each group grows. If the group of plants that were exposed to sunlight grows faster, this provides evidence that supports your hypothesis. If the plants that were in the shade grow faster, or if there is no significant difference in the growth rates of the two groups, this provides evidence against your hypothesis. Overall, hypothesis testing is a way of using evidence and data to evaluate the likelihood of different ideas and theories.

Null vs alternative hypothesis 

In hypothesis testing, a null hypothesis is a prediction that there will be no difference or change in the thing you are studying. For example, if you have a hypothesis that a certain type of plant will grow faster in sunlight than in the shade, the null hypothesis would be that there will be no difference in the growth rates of the plants in sunlight and shade. An alternative hypothesis is a prediction that there will be a difference or change in the thing you are studying. In this case, the alternative hypothesis would be that the plants exposed to sunlight will grow faster than the plants in the shade. To test these hypotheses, you would set up two groups of plants, expose one group to sunlight and the other group to shade, and then measure the growth rates of each group. If the plants in the sunlight grow faster, this provides evidence in favor of the alternative hypothesis. If the plants in the shade grow faster, or if there is no significant difference in the growth rates of the two groups, this provides evidence in favor of the null hypothesis. Overall, the null and alternative hypotheses are two possible predictions that you can test using data and evidence.