**asic Science Biostatistics** is the study of mathematical discipline of statistics to the field of health sciences, specifically biology and epidemiology. **Medicos Library** has provided high standard Basic Science Biostatistics Notes by Dr. Yousif Abdallah Hamad.

### Summary of Notes:

**Significance tests**

A null hypothesis (H0) states that two treatments are equally effective (and is hence negatively phrased). A significance test uses the sample data to assess how likely the null hypothesis is to be correct. The null hypothesis is always that there is no difference between the variables we would like to test for a difference.

For example:

- ‘there is no difference in the prevalence of colorectal cancer in patients taking low-dose aspirin compared to those who are not’
- The alternative hypothesis (H1) is the opposite of the null hypothesis, i.e. There is a difference between the two treatments The p value is the probability of obtaining a result by chance at least as extreme as the one that was actually observed, assuming that the null hypothesis is true. It is therefore equal to the chance of making a type
- I error (see below). the p-value is the probability of obtaining the observed results or results which are more extreme if the null hypothesis is true
- In case of the p value is below 0.05 and we accept the alternative hypothesis in favour of the null hypothesis Two types of errors may occur when testing the null hypothesis

**Type I**: the null hypothesis is rejected when it is true – i.e. Showing a difference between two groups when it doesn’t exist, a false positive. This is determined against a preset significance level (termed alpha). As the significance level is determined in advance the chance of making a type I error is not affected by sample size. It is however increased if the number of end-points are increased. For example if a study has 20 end-points it is likely one of these will be reached, just by chance.

**Type II**: the null hypothesis is accepted when it is false – i.e. Failing to spot a difference when one really exists, a false negative. The probability of making a type II error is termed beta. It is determined by both sample size and alpha.

## Advice form Dr. Yousif Abdallah Hamad

**How to use the notes to study for MRCP:**

- Initially, you need to skim through the notes at least twice to build up an idea about the syllabus of MRCP. Highlight any portion that is difficult so that you can concentrate on that during your revision.
- Next proceed to the question banks. You can choose to do Passmedicine, onexamination or Pastest. I usually recommend students to do Passmedicine and the Pastest.
- As you go through the questions make a super-revised notes of your own. Write down in one sentence what you learned from the question you just attempted.
- If you get any question wrong or you get confused then return to the notes and re-read one more time before attempting the question again. And write down the point in red in you revision notes so that you can skim through it easily during your revision.
- I have highlighted some points in yellow and green to help you concentrate on those points. As you go through passmedicine and pastest, you can highlight the points further to help in your revision.
- During your revision before the main exam, only read the highlighted portions including those that you highlighted when practicing the question bank. And also read your super-revised notes that you made from the question banks.

I believe these method has worked for many students and will help you in your journey to be successful in MRCP part 1 and as well as build your basics for Part 2.

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