Module 7: Basics Of Biostatistics

The given formula for calculating risk is correct. Risk is calculated by dividing the number of new cases by the population at risk. This formula helps in quantifying the likelihood of an event or condition occurring within a specific population. Therefore, the answer is true.

The given statement is true. The rate is calculated by dividing the number of new cases by the person-time at risk. This formula is commonly used in epidemiology to measure the incidence or occurrence of a disease in a population. By dividing the number of new cases by the person-time at risk, we can determine the rate at which new cases are occurring in a specific population over a specific period of time.

The formula given, odds = cases/non-cases, is a correct representation of how odds are calculated. Odds are the ratio of the number of cases to the number of non-cases. Therefore, the answer is true.

If all patients are 45 years old, there is no variation in age among the patients. This means that the standard deviation (SD), which measures the dispersion or spread of data, will be zero. Zero indicates that all the data points are the same, in this case, 45 years old.

Standard deviation is a statistical measure that quantifies the amount of variation or dispersion in a set of data. It provides information about how spread out the data points are from the mean or average. A higher standard deviation indicates that the data points are more spread out, while a lower standard deviation indicates that the data points are closer to the mean. Therefore, option A) "measure of spread of data" is the correct answer.

The given information states that patients in the control group required more cataract surgery than those in the intervention group. The p-value is given as 0.01, which is less than the conventional threshold of 0.05. This means that there is a low probability of observing the difference in surgery rates between the two groups by chance alone. Therefore, the result is statistically significant, indicating that there is a genuine difference between the two groups.

Normal law refers to the concept of normal distribution, which is a statistical distribution that is symmetrical and bell-shaped. It is commonly observed in various biological variables such as height, weight, and blood pressure. This means that the majority of biological variables tend to follow a normal distribution pattern, where the data is evenly distributed around the mean. Therefore, option B is the correct answer as it accurately describes the concept of normal law.

Percentage may be used to hide the true size of the data in small samples because when dealing with a small sample size, even a small change in the number of occurrences can result in a significant difference in the percentage. This can be misleading as it may give the impression that a certain event or outcome is more or less common than it actually is. In larger samples, the impact of small changes is diluted, making it harder to manipulate the data using percentages. Therefore, the use of percentages to hide the true size of the data is more effective in small samples.

The mean weight of the patients is 65 kg, and the standard deviation is 5 kg. In a normal distribution, approximately 68% of the data falls within one standard deviation of the mean, approximately 95% falls within two standard deviations, and approximately 99.7% falls within three standard deviations. Since the standard deviation is 5 kg, two standard deviations would be 10 kg. Therefore, 95% of the subjects will weigh between 65 - 10 kg and 65 + 10 kg, which is 55 kg and 75 kg respectively.

The disadvantage of converting numerical data to categorical data is the loss of data. When converting numerical data to categories, we are essentially grouping the data into distinct categories or intervals. This can result in the loss of specific numerical values and the granularity of the data. This loss of data can limit the accuracy and precision of the analysis and may lead to a loss of valuable information that could have been obtained from the original numerical data.