The t test is the most common null hypothesis test for this type of statistical relationship. The one-sample t test, the dependent-samples t test, and the independent-samples t test are three forms of t tests that are employed for slightly distinct research designs in this area.
Hypothesis testing is the act of making an observation, formulating a question based on the information gathered, and then attempting to answer the problem using the scientific method, just as you learned in science class.
The basic goal of statistics is to prove or disprove a theory.
For example, you might conduct research and discover that a particular medicine is useful in the treatment of headaches. No one will believe your findings if you can't repeat the experiment.
Hypothesis testing is used to determine if the null hypothesis (no difference, no effect) may be accepted or rejected. The research hypothesis can be accepted if the null hypothesis is rejected.
A hypothesis is frequently referred to as a "informed guess" regarding a particular parameter or population. After it has been defined, data can be gathered to see if it provides sufficient evidence to support the hypothesis.
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Sunita Singhal
5
please provide notes also in pdf
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Montu Mali
4
nice ☺️👍
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Abdul Samed
5
please provide course notes
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Shashi Kumar
5
great resource to learn data science in hindi. but in this particular video lecture there is a mistake....actually mutually exclusive event can never be independent event.
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Nikhil Fapale
5
it really amazing to study....and easily understand difficult concepts...i hope you make more video on like power bi and nueral network model....its really helpful....thank you for these
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