Question

1)explain the four major steps involved in Hypothesis Testing. which step you feel will be the most important to the process and why.

2) Give a real life example of how you might use hypothesis testing.

Answer 1

1) Ans: we use test hypothesis when we have to compare two groups.

The four steps are as follows:

1) specify null and alternative hypothesis: The null hypothesis H₀ is a statement of no effect, relationship, or difference between two or more groups or factors. In research studies, a researcher is usually interested in disproving the null hypothesis.

The alternative hypothesis H₁is the statement that there is an effect or difference. This is usually the hypothesis the researcher is interested in proving.

2) To set the significance level: The significance level is generally set at 0.05. it is denoted by alpha. This means that there is a 5% chance that you will accept your alternative hypothesis when your null hypothesis is actually true. The smaller the significance level, the greater the burden of proof needed to reject the null hypothesis, or in other words, to support the alternative hypothesis.

3) To calculate the test Statistics and corresponding p- value:  

Hypothesis testing generally uses a test statistic that compares groups or examines associations between variables. When describing a single sample without establishing relationships between variables, a confidence interval is commonly used.

The p-value describes the probability of obtaining a sample statistic as or more extreme by chance alone if your null hypothesis is true. This p-value is determined based on the result of your test statistic. Your conclusions about the hypothesis are based on your p-value and your significance level.

4) test criteria and conclusion: after calculating test Statistics and p- value we, we have to set a criteria for rejecting the null hypothesis.

If p- value < alpha, then we reject the null hypothesis.

If p- value > alpha then we accept null hypothesis.

For me , the first step is more important since if we fail to make a right statement about null and alternative hypothesis then there's no importance of further steps.

2) Ans: Example

Null hypothesis: There is no association between injury type and whether or not the patient received an IV in the prehospital setting.

Alternative hypothesis: There is an association between injury type and whether or not the patient received an IV in the prehospital setting.

Significance level: let the significance level alpha is 5%.

Test Statistics and p- value: let p- value= 0.01

Conclusion: here since p value (0.01) < alpha(0.05), hence we reject the null hypothesis that means there is an association between injury type and whether or not the patient received an IV in the prehospital settings.