This data is in a 2 × 2 contingency table so a chi square test can be used. There is a special chi squared formula that gives a value that can be looked up in a table giving the p value.

Since we are comparing proportions not means, the Student’s t test CANNOT be used.

There is no linear regression to plot so Pearson’s co-efficient cannot be calculated.

Nothing is so obvious that no statistical analysis is needed.

Chi-square test is used to determine the statistically significant different between categorical variables. It also determines the difference between expected frequencies and the observed frequencies.

Mann Whitney U test is used to determine the statistically significant different between two independent groups.

Wilcoxon’s test is the test of dependency. it determines the statistically significant difference between two dependent groups.

Student t-test is one of the most commonly used method to test the hypothesis. It determines the significant difference between the means of two different groups.

ANOVA (analysis of variance) is similar to student’s t-test.

ANOVA is a statistical method used to determines the statistically significant difference between the mean of more than two group. In this experiment as we are dealing with three different group, ANOVA is most suitable test to determine the difference between each groups.

Attributable proportion is the proportion of disease that is caused due to exposure. It refers to the proportion of disease that would be eradicated from a particular population if the disease rate was diminished to match that of the unexposed group.

Risk ratio (relative risk) compares the probability of an event in an exposed (experimental) group to that of an event in the unexposed (control) group. Thus two are not the same.

The attributable risk is the rate of a disease in an exposed group to that of a group that has not been exposed to it i.e. how many deaths did the exposure cause.

Case control studies in particular are prone to recall bias, people who are suffering from COPD might sometimes relate the ailment to marijuana usage in past and hence contrary to the control group, they are more able to describe to what extent they have been using the drug in the past.

As recommended, all the doctors should make sure that there practice is based on evidence and thus it is paramount that the doctors learn to appraise the paper in a critical manner i.e. ability to detect any potential source of bias.

Detection Bias: Outcomes are more looked for in one group than the other.

Observer Bias: Subjectivity of observers regarding the outcome.

Publication bias: Not publishing the results of a valid study just because they are negative or uninteresting can be termed as publication bias.

Recall bias: Recall bias is specifically appropriate to the case control studies that is when ever the memories retrieved by the participants differ in accuracy.

Response Bias: The participants that filled out the response forms containing information that was going to be used for a trial, don’t represent the target population.

Phase 0 trials assist the scientists in studying the behaviour of drugs in humans by micro dosing patients. They are used to speed up the developmental process. They have no measurable therapeutic effect and efficiency.

The Number Needed to Treat (NNT) is the number of patients you need to treat to prevent one additional bad outcome. For example, if a drug has an NNT of 5, it means you have to treat 5 people with the drug to prevent one additional bad outcome.

To calculate the NNT, you need to know the Absolute Risk Reduction (ARR); the NNT is the inverse of the ARR:

NNT = 1/ARR

Where ARR = CER (Control Event Rate) – EER (Experimental Event Rate).

NNTs are always rounded up to the nearest whole number.

In this case, the NNT can be computed as follows:

ARR = 10% – 5% = 0.05

NNT = 1/0.05 = 20

Being the part of a meta analysis, forest plots are more valued as evidence then randomised control trials.

The notion that forest plots can only be used if the results are substantial is not true. They are good indicators of the significance of the data. If the diamond intersects the central line, the data is rendered significant. It also aggregates means and confidence intervals from studies conducted in the past which makes the study much more reliable as errors associated with individual studies tend to have less of an impact in this way.

The suggestion that forest plots are primarily used for qualitative data is factually incorrect. Forest plots require numerical values to function.

All in all, forest plots help us in determining whether or not there is a significant trend in that particular field of study.

The Delphi is a group facilitation technique that seeks to obtain consensus on the opinions of `experts’ through a series of structured questionnaires (commonly referred to as rounds). By using successive questionnaires, opinions are considered in a non-adversarial manner, with the current status of the groups’ collective opinion being repeatedly fed back. Studies employing the Delphi make use of individuals who have knowledge of the topic being investigated

An epidemic is declared when the increase in a give disease is above a certain level in a specific interval of time.

An endemic is the general, usual level of a disease in a population at a particular time.

A pandemic is an epidemic that is spread across many countries and continents.

99.7% of the values within 3 standard deviations of the mean.

For 99.7% confidence interval, you can find the range as follows:

1. Multiply the standard error by 3.

2. Subtract the answer from mean value to get the lower limit.

3. Add the answer obtained in step 1 from the mean value to get the upper limit.

For a confidence interval of 68%, multiply the standard error with 1 and repeat the process. For a 95% confidence interval, Standard Error is multiplied by 1.96 to get the interval.