BIO401 Midterm Past Papers Fall 2024 by Sayyeda Masooma Hassan

BIO401

(Fall 2024)

By

Sayyeda Masooma Hassan

VU EXPERT ZOOLOGISTS

Q01. Define biostatistics:

The use of statistical methods to solve the biological problems. It is also called biometry.

Q2. Population and Sample:

Population refers to the entire group of individuals that share a common characteristic and are the focus of a study at a particular time. In population the measurable quantity is called Parameter. While Sample is a subset of the population that is selected for the actual analysis. Sampling is Often done when it is impossible to study the entire population. In sample the measurable quantity is called statistic.

Q3. Hypothetical Population?

A hypothetical population is a population that is imaginary or doesn’t exist in a solid form. It is the opposite of an existing population. Here are some examples of hypothetical populations:

1. The outcomes of an experiment that is repeated infinitely
2. The outcomes of tossing a coin infinitely, resulting in a hypothetical population of “heads” and “tails”

Subjective Questions

Q4. Note on Survey?

Surveys A method to collect direct feedback and information from a target audience. Surveys can be conducted online, over the phone, or face-to-face.

Q5. Finite Population (Countable):

• The finite population is also known as a countable population in which the population can be counted.
• For statistical analysis, the finite population is more advantageous.
• Example: employees of a company.

Infinite Population (Uncountable):

• The population in which the counting of units in the population is not possible.
• It is less advantageous in statistical analysis
• Example: Number of germs in the patient’s body.

Q6. Difference between Parameter and Statistic?

A parameter is a numerical characteristic of a population. It is a fixed value that describes some aspect of the population. For example, the average blood pressure of all adults in a specific region is a parameter. A statistic is a numerical characteristic of a sample. It is used to estimate or infer the Corresponding parameter of the population. For instance, the average blood pressure of a sample of 100 adults from the same region is a statistic.

Q7. Detail note on Data?

Data refers to information collected, observed, or measured from population or sample during the study. This information can take various forms, including numerical values, categorical labels, or descriptive details, and it serves as the foundation for statistical analysis. Biostatisticians use data to draw conclusions and derive meaningful insights about biological phenomena, health outcomes, or medical interventions. There are two types of data:

1. Primary Data:

• This refers to data that is collected firsthand directly from the source.
• Common methods of collecting primary data include surveys, interviews, experiments, and Observations.
• Primary data is original, providing a high degree of relevance and specificity to the research question.
• It is expensive and take more time.

2. Secondary Data:

• The that has already been collected by someone else for a different purpose.
• Researchers utilize existing sources, such as published studies, government reports, or datasets, to obtain secondary data
• Secondary data is less specific to the researcher’s needs and may not perfectly align with the study objectives.
• It is not expensive and time-saving way to access a large volume of information.

Q8. Detail note on Variable?

A variable is a characteristic that can be measured and that can assume different values. There are two types of variable:

1. Qualitative variable:

Qualitative variables are non-numeric and describe qualities or characteristics. Examples

include Gender, blood type, place of birth, ethnic group, type of drug etc.

2. Quantitative variable:

A quantitative variable is one that can be measured and expressed numerically. They have further two types: a) Discrete Variable: Discrete variables are numeric variables that can only take specific, distinct

Values, often counted in whole numbers and cannot be subdivided into smaller units. Examples include the number of patients in a clinic, the number of red blood cells. b) Continuous Variable: Continuous variables are numeric variables that can take any value within

A range and can be measured with a high level of precision. These variables can be further

Subdivided into smaller and smaller units, and they are often associated with measurements

Rather than counts. Examples include height, weight, blood pressure, or temperature.