Question

What is the aim of hypothesis testing?

What does hypothesis testing achieve that could not be otherwise achieved?

How does hypothesis testing help support the fields that employ the scientific method?

Besides hypothesis testing, are there alternative ways to validate the research findings?

Answer 1

What is the aim of hypothesis testing?
Ans- Step 1

Hypothesis:

Hypothesis is an assumption about the parameter of the population which will be made on the limited evidence as the start value to proceed for further investigation, and the assumption may or may not be true.

In testing the hypothesis is of two types. The two types are:

Null hypothesis (H0)

Alternative hypothesis (H1)

Step 2

Null and alternative hypotheses:

Null hypothesis:

Null hypothesis is a statement which is tested for statistical significance in the test. The decision criterion indicates whether the null hypothesis will be rejected or not in the favor of alternative hypothesis.

What does hypothesis testing achieve that could not be otherwise achieved?

Ans - start with an example

An economist wants to determine whether the monthly energy cost for families has changed from the previous year, when the mean cost per month was $260. The economist randomly samples 25 families and records their energy costs for the current year. (The data for this example is FamilyEnergyCost and it is just one of the many data set examples that can be found in Minitab’s Data Set Library.)

Descriptive statistics: energy cost

Variable energy cost
Total count -25
Mean -330.6
SE mean - 30.8
ST. deviation - 154.2

I’ll use these descriptive statistics to create a probability distribution plot that shows you the importance of hypothesis tests. Read on!

The Need for Hypothesis Tests

Why do we even need hypothesis tests? After all, we took a random sample and our sample mean of 330.6 is different from 260. That is different, right? Unfortunately, the picture is muddied because we’re looking at a sample rather than the entire population.

Sampling error is the difference between a sample and the entire population. Thanks to sampling error, it’s entirely possible that while our sample mean is 330.6, the population mean could still be 260. Or, to put it another way, if we repeated the experiment, it’s possible that the second sample mean could be close to 260. A hypothesis test helps assess the likelihood of this possibility!

How does hypothesis testing help support the fields that employ the scientific method?

Ans- Scientists often validate the significance of a hypothesis by comparing its validity against that of a null hypothesis. In most cases, the comparison is founded on empirical evidence. In this light, hypothesis testing is a significant means through which scientific conclusions are tested and validated.

Besides hypothesis testing, are there alternative ways to validate the research findings?

Ans-Other than hypothesis testing, scientists can also use rationalism. As the name suggests, this method applies logic and reasoning to test and validate conclusions.