Hypothesis Testing

Testing an assumption regarding a population parameter involving a sample data based on a large population.

A hypothesis test guarantees the working of a primary hypothesis. The methodology of the testing process depends on the nature of the sample data and the rationale behind analysis. Until a null hypothesis is achieved, an analyst is expected to repeat the process until a true hypothesis is received. A mutually exclusive alternate hypothesis is also drawn from the sample with the objective of extracting a conclusion. The basic structure followed is:

Defining research hypothesis
Include variables to study
Set null and alternative hypothesis
One or two-tailed predictions
Select statistical test
Run test to get output

Hypothesis testing services we provide

We, at PhDstatistics know that understanding these terminologies could be difficult and thus we provide support in services such as

Stating the hypothesis

To test if a hypothesis is true, one has to devise a null hypothesis and an alternate hypothesis. The alternative hypothesis is designed with the objective of nullifying itself. Our experienced researchers develop the right hypothesis statement scrutinizing the available knowledge based on the topic of study and speculate the functional areas to make sure of its working.

Data collection and summarizing

A researcher collects the sample data based on a population or universe and testing hypotheses needs summarizing of the collected samples. We apply statistical tools to help categorize them under sample mean, sample mean and sample standard deviation. This process is called Test statistic and is vital to run specific tests. We use them to check presumptions to run tests.

Evidence assessment

We access the sample data provided by the researcher and validate the hypothesis if it's true. This step is carried after executing the plan of summarizing and physically analysing the data. We draw conclusions after observing and assessing the resulting data. We use this evidence as the basis of testing the null-hypothesis. The conclusions are drawn based on the significance of the test.

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