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Questions and Answers
Which type of sampling involves selecting groups based on pre-existing characteristics rather than individual attributes?
Which type of sampling involves selecting groups based on pre-existing characteristics rather than individual attributes?
- Stratified sampling
- Systematic sampling
- Simple random sampling
- Cluster sampling (correct)
Quantitative variables can only take on categorical values.
Quantitative variables can only take on categorical values.
False (B)
What is a confidence interval?
What is a confidence interval?
A range of values used to estimate a population parameter with a certain level of confidence.
In systematic sampling, every ___ individual or item is measured or selected.
In systematic sampling, every ___ individual or item is measured or selected.
Match the sampling methods with their correct definitions:
Match the sampling methods with their correct definitions:
What is the size of a sample denoted by?
What is the size of a sample denoted by?
A census surveys only a part of the population.
A census surveys only a part of the population.
What is the main purpose of statistics?
What is the main purpose of statistics?
The complete collection of information from all individuals in a study is known as the __________.
The complete collection of information from all individuals in a study is known as the __________.
Match the following statistical terms with their definitions:
Match the following statistical terms with their definitions:
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Study Notes
Introduction to Statistics
- Statistics encompasses the collection, organization, analysis, and interpretation of data.
- It plays a crucial role in decision-making amidst uncertainty.
- Biostatistics focuses specifically on data from biological and medical contexts.
Key Terminologies in Statistics
- Population (N): A complete set of individuals or items of interest in a study.
- Entire data collected for all individuals is termed population data.
- A census gathers data from every individual in the population.
- Sample (n): A subset of the population providing partial information.
- Sample size (n) represents the number of observations from the population.
- Parameter: A numerical value that characterizes a population's attributes (e.g., mean, median, variance).
- Statistic: An estimate derived from sample data representing the population parameter.
Types of Statistics
- Descriptive Statistics: Methods used for summarizing and organizing data.
- Techniques include stem-and-leaf plots, frequency tables, contingency tables, bar charts, pie charts, histograms, and scatter plots.
- Inferential Statistics: Involves interpreting descriptive statistics to make population-related conclusions.
- Key methods include confidence intervals and hypothesis testing.
Individuals and Variables
- Individuals: The subjects (people, places, things) from which data is collected.
- Variables: Characteristics of individuals that can be observed or measured.
- Qualitative Variables: Categorical data that classifies individuals into groups.
- Quantitative Variables: Numerical data suitable for mathematical operations.
Random Variables
- Discrete Random Variable: Takes on finite, distinct outcomes (e.g., counts).
- Continuous Random Variable: May assume an infinite set of outcomes (e.g., measurements).
Sampling Techniques
- Simple Random Sampling: Each combination of individuals has an equal chance of selection, ensuring randomness.
- Cluster Sampling: Involves selecting groups based on pre-existing categories without regard to individual characteristics.
- Systematic Sampling: Every k-th individual in the population is selected, introducing a systematic method of choosing samples.
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