Podcast
Questions and Answers
Match the following terms with their definitions:
Match the following terms with their definitions:
Population = An entire group to be studied Sample = A selection or subset of members from the population Element = A single member of a population or sample Variable = A characteristic of the members of a population
Match the following types of statistics with their purpose:
Match the following types of statistics with their purpose:
Descriptive Statistics = Organizing and summarizing information Inferential Statistics = Drawing conclusions about a population from a sample Census = Collecting data from ALL members of a population Sampling Survey = Collecting data from a sample of a population
Match the types of variables with their descriptions:
Match the types of variables with their descriptions:
Qualitative Variable = Measures a non-numerical characteristic Quantitative Variable = Measures a characteristic that can be ranked or ordered Discrete Quantitative Variable = Can only take on certain values, usually integers Continuous Quantitative Variable = Can take on any value within an expected range
Match the types of data with their definitions:
Match the types of data with their definitions:
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Match the following data collection methods with their characteristics:
Match the following data collection methods with their characteristics:
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Match the key terms with their respective notations:
Match the key terms with their respective notations:
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Match the statistical concepts with their examples:
Match the statistical concepts with their examples:
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Match the sampling methods with their descriptions:
Match the sampling methods with their descriptions:
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Match the following random sampling designs with their descriptions:
Match the following random sampling designs with their descriptions:
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Match the following non-random sampling designs with their definitions:
Match the following non-random sampling designs with their definitions:
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Match the following experimental designs with their characteristics:
Match the following experimental designs with their characteristics:
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Match the following descriptions of sampling designs with their types:
Match the following descriptions of sampling designs with their types:
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Match the experimental design terms with their definitions:
Match the experimental design terms with their definitions:
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Match the types of designs with their descriptions:
Match the types of designs with their descriptions:
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Match the following sampling methods with their intended use:
Match the following sampling methods with their intended use:
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Match the terms related to groups in an experiment:
Match the terms related to groups in an experiment:
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Match the following sampling terms with their explanations:
Match the following sampling terms with their explanations:
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Match the principles of experimental design with their purposes:
Match the principles of experimental design with their purposes:
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Match the following statistical principles with their associated sampling designs:
Match the following statistical principles with their associated sampling designs:
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Match the block types with their characteristics:
Match the block types with their characteristics:
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Match the following types of sampling surveys to their features:
Match the following types of sampling surveys to their features:
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Match terms with related aspects of biases in experiments:
Match terms with related aspects of biases in experiments:
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Match the examples of experimental conditions to their definitions:
Match the examples of experimental conditions to their definitions:
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Match the terms with the appropriate experimental processes:
Match the terms with the appropriate experimental processes:
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Match the daily caloric intake ranges with their corresponding treatment groups:
Match the daily caloric intake ranges with their corresponding treatment groups:
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Match the daily exercise levels with their respective treatment groups:
Match the daily exercise levels with their respective treatment groups:
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Match the treatment group descriptions with their calorie and exercise levels:
Match the treatment group descriptions with their calorie and exercise levels:
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Match the potential biases with their explanations:
Match the potential biases with their explanations:
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Match the treatment levels with their group counts:
Match the treatment levels with their group counts:
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Study Notes
Basic Statistics Definitions
- Population: The entire group being studied.
- Population size (N): The total number of elements in the population.
- Sample: A subset of the population used for analysis and projection back to the population.
- Sample size (n): The number of elements in the sample; n ≤ N.
- Descriptive Statistics: Mathematical methods for organizing and summarizing information.
- Inferential Statistics: Methods for drawing conclusions, and measuring the reliability of conclusions, about a population based on a sample.
- Element/Experimental Unit: A single member of a population or sample.
- Sampling: The process of selecting elements from a population to create a sample.
- Sampling Design: A specific methodology for selecting elements for the sample.
- Qualitative Variable: Measures non-numerical characteristics.
- Quantitative Variable: Measures characteristics that can be ranked or ordered numerically.
- Discrete Quantitative Variable: Can only take on certain, usually integer, values.
- Continuous Quantitative Variable: Can take on any value within a given range.
Data Types
- Univariate Data: Data collected on a single variable.
- Bivariate Data: Data collected on two variables.
- Multivariate Data: Data collected on three or more variables.
- Cross-Sectional Data: Data collected at a single point in time.
- Time-Series Data: Data collected over a period of time.
- Census: Data collected from all members of a population.
- Sampling Survey: Data collected from a sample of a population.
Sampling Designs (Random to Least Random)
- Simple Random Sampling: Every element has an equal chance of being selected.
- Stratified Random Sampling: Random selection from subgroups (strata) proportional to their representation in the population.
- Cluster Sampling: Randomly select clusters, then include all elements within the selected clusters.
- Systematic Sampling: Select every kth element from the population.
Non-Random Sampling Designs
- Convenience Sampling: Selecting easily available elements.
- Judgment Sampling: Selecting elements based on the researcher's judgment.
Experimental Designs
- Observational Studies: Researchers observe characteristics and take measurements.
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Designed Experiments: Researchers employ treatments and controls to observe characteristics/outcomes.
- Treatment: Experimental condition
- Response Variable: Outcome of interest
- Factor: Variable whose effect is of interest
- Levels: Possible values of a factor
- Treatment Group: A group receiving a specific treatment.
- Control Group: Group not receiving treatment, or receiving baseline treatment.
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Principles of Experimental Design:
- Control: For effects not of interest
- Randomization: Avoid unintentional biases in group selection.
- Replication: Sufficient subjects to ensure detection of treatment differences.
- Completely Randomized Design (CRD): Experimental units assigned randomly to treatments.
- Randomized Block Design: Groups (blocks) of experimental units are created to minimize variance among a given group, then treatments are assigned to units within these groups randomly
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Description
Test your knowledge of key concepts in basic statistics with this quiz. From understanding populations and samples to differentiating between descriptive and inferential statistics, this quiz covers essential definitions. Sharpen your skills and gain a better grasp of statistical terminology.