Podcast
Questions and Answers
What is statistics?
What is statistics?
A collection of methods for planning experiments, obtaining data, and then organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions based on the data.
What is a population in statistics?
What is a population in statistics?
The complete collection of all elements (scores, people, measurements, etc.) to be studied.
What is a census?
What is a census?
The collection of data from every element in a population.
What is a sample?
What is a sample?
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What is a parameter?
What is a parameter?
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What is a statistic?
What is a statistic?
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What is quantitative data?
What is quantitative data?
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What is qualitative data?
What is qualitative data?
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What is discrete data?
What is discrete data?
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What is continuous data?
What is continuous data?
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What is nominal level of measurement?
What is nominal level of measurement?
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What is ordinal level of measurement?
What is ordinal level of measurement?
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What is interval level of measurement?
What is interval level of measurement?
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What is ratio level of measurement?
What is ratio level of measurement?
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What is a self-selected survey?
What is a self-selected survey?
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What is an observational study?
What is an observational study?
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What is an experiment?
What is an experiment?
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What is confounding?
What is confounding?
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What is a random sample?
What is a random sample?
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What is a simple random sample?
What is a simple random sample?
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What is stratified sampling?
What is stratified sampling?
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What is systematic sampling?
What is systematic sampling?
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What is cluster sampling?
What is cluster sampling?
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What is convenience sampling?
What is convenience sampling?
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What is sampling error?
What is sampling error?
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What is a nonsampling error?
What is a nonsampling error?
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Study Notes
Statistics Overview
- Statistics encompasses methods for designing experiments and collecting data, as well as organizing, summarizing, analyzing, and interpreting this data to draw conclusions.
Key Terminology
- Population: Total collection of all elements (scores, people, measurements) targeted for study.
- Census: Data collection that covers every element within a population.
- Sample: A subset of elements selected from a population for analysis.
Measurements
- Parameter: A numerical value that describes a characteristic of a population.
- Statistic: A numerical value that describes a characteristic of a sample.
Data Types
- Quantitative Data: Numeric data representing counts or measurements.
- Qualitative Data: Data categorized by non-numeric characteristics.
- Discrete Data: Derived from finite or countable values, including whole numbers.
- Continuous Data: Associated with a continuous scale, allowing for an infinite number of possible values without gaps.
Levels of Measurement
- Nominal Level: Data categorized by names or labels without a natural ordering.
- Ordinal Level: Data can be ordered but differences may be meaningless or undetermined.
- Interval Level: Offers meaningful differences between values but lacks a true zero point.
- Ratio Level: Similar to interval but includes an inherent zero, making both differences and ratios meaningful.
Survey and Study Methods
- Self-Selected Survey: Participants choose to be included in the survey.
- Observational Study: Involves observing subjects without manipulating variables.
- Experiment: Involves applying a treatment to subjects and observing outcomes.
Sampling Techniques
- Confounding: Difficulty in distinguishing effects of two or more variables simultaneously.
- Random Sample: Each member of a population has an equal chance of selection.
- Simple Random Sample: Every possible sample of a specified size has the same chance of being chosen.
- Stratified Sampling: Population divided into strata based on shared characteristics, with a sample drawn from each stratum.
- Systematic Sampling: Selecting a starting point and every kth member thereafter.
- Cluster Sampling: Dividing the population into clusters, randomly selecting clusters, and including all members from chosen clusters.
- Convenience Sampling: Using readily available results without systematic selection.
Sampling Errors
- Sampling Error: Discrepancy between sampled results and actual population results due to random chance.
- Nonsampling Error: Errors resulting from incorrect data collection, recording, or analysis, including biases in sample selection or measurement errors.
Studying That Suits You
Use AI to generate personalized quizzes and flashcards to suit your learning preferences.
Description
Test your knowledge with these flashcards on key concepts from Statistics Chapter 1. Review important terms like 'statistics', 'population', and 'census' to reinforce your understanding. Perfect for students preparing for exams or anyone looking to brush up on basic statistical concepts.