F: Chapter 3: The Nature of Statistics

Question 1

1) Census:

Answer 1

Collects data from entire population.

It aims to gather information about each individual or unit within the population.

Question 2

2) Cluster Sampling:

Answer 2

Cluster sampling is a method of dividing a population into randomly selected clusters for surveying when the entire population is impractical or costly.

Question 3

2) Sample

Answer 3

Subset of population for study.

that is chosen to represent the entire group.

It’s used for analysis and making inferences about the larger population based on the characteristics of the sample.

Question 4

1) Population

Answer 4

Entire group being studied.

A population refers to the entire group of individuals, items, or units that a study or analysis is focused on.

Question 5

5) Systematic Bias/ systematic error:

Answer 5

• Consistent error in measurements or estimates.
• Arises from flaws in research design or analysis.
• Affects measurements in a specific direction.
• Can lead to inaccurate or misleading results.

Question 6

6) Parameter

Answer 6

is a fixed value, often derived from census or sample data, that provides insights into a population’s characteristics.

Parameter(s) of a Function:
* Values influencing a function’s behavior.
* Constants in mathematical or statistical models.
* Define characteristics, shape, and position of function.
* Examples: Slope and intercept in linear equations.

Question 7

Parameter(s) of a Function:

Answer 7

• Values influencing a function’s behavior.
• Constants in mathematical or statistical models.
• Define characteristics, shape, and position of function.
• Examples: Slope and intercept in linear equations.

Question 8

7) Sampling Error:

Answer 8

is the discrepancy between sample results and true population values, arising from random selection of samples.

Question 9

8) Sampling Frame:

Answer 9

is a crucial step in the sampling process, selecting elements from which a sample is selected to accurately represent the population.

Question 10

9) Simple Random Sample:

Answer 10

is a sampling technique that ensures equal chance of selection for each member of the population,

minimizing bias and often using random number generators.

Question 11

10) Stratified Sampling:

Answer 11

Stratified sampling involves dividing the population into distinct subgroups or strata based on certain characteristics. Then, samples are randomly selected from each stratum, ensuring representation of various subgroups.