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Questions and Answers
What is a double-blind experiment?
What is a double-blind experiment?
Undercoverage occurs when the proportion of one segment of the population is higher in a sample than it is in the population.
Undercoverage occurs when the proportion of one segment of the population is higher in a sample than it is in the population.
False
What is a census?
What is a census?
A list of all individuals in a population along with certain characteristics of each individual.
What occurs when the effects of two or more explanatory variables are not separated?
What occurs when the effects of two or more explanatory variables are not separated?
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A designed experiment occurs when a researcher simply observes without manipulating any variables.
A designed experiment occurs when a researcher simply observes without manipulating any variables.
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What does it mean if a variable is at the ratio level of measurement?
What does it mean if a variable is at the ratio level of measurement?
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What is continuous data?
What is continuous data?
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What are quantitative data?
What are quantitative data?
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What is a sample?
What is a sample?
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What is the mean?
What is the mean?
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What is inferential statistics?
What is inferential statistics?
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Define descriptive statistics.
Define descriptive statistics.
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What is a parameter?
What is a parameter?
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What is a placebo?
What is a placebo?
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What is a convenience sample?
What is a convenience sample?
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A cluster sample involves selecting individuals from multiple groups randomly.
A cluster sample involves selecting individuals from multiple groups randomly.
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What is nonresponse bias?
What is nonresponse bias?
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What is a lurking variable?
What is a lurking variable?
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Study Notes
Experimental Design
- A double-blind experiment keeps both the experimental unit and researcher unaware of treatment assignments to avoid bias.
- Confounding occurs when multiple explanatory variables affect the response variable, complicating the interpretation of results.
- A designed experiment involves researchers assigning treatments to individuals to investigate the impact on response variables.
Sampling Methods
- Undercoverage leads to sampling bias; certain population segments are inadequately represented in the sample.
- A census is a complete list of individuals in a population with specific characteristics.
- A sample is a subset of a population that is studied to draw conclusions about the larger group.
- Stratified sampling involves dividing the population into homogeneous groups (strata) and randomly sampling from each stratum.
Data Measurement Levels
- Nominal level of measurement categorizes variables without a ranked order.
- Ordinal level provides a ranked order but doesn’t quantify differences between ranks.
- Interval level entails ordered values where differences are meaningful but lack a true zero point.
- Ratio level includes all interval properties, with meaningful ratios and an absolute zero indicating the absence of quantity.
Types of Variables
- Continuous data correspond to continuous variables that can take an infinite number of values.
- Discrete data are observations from a discrete variable that has finite or countable values.
- Qualitative data categorize characteristics or qualities of individuals.
- Quantitative data represent measurable quantities and can be continuous or discrete.
Statistical Concepts
- Statistics involves collecting, organizing, summarizing, and analyzing data to draw conclusions with confidence.
- A parameter is a numerical summary of a population, while a statistic summarizes sample data.
- Descriptive statistics organize and summarize data, while inferential statistics extend findings from a sample to a population and assess reliability.
Research Process
- Clearly identify the research objective to define the population and questions of interest.
- Collect data meticulously to ensure the validity of conclusions, often relying on samples due to logistical challenges in studying entire populations.
Observational Studies
- An observational study measures the response variable without influencing either the response or explanatory variables, allowing for natural behavior analysis.
- Lurking variables can introduce bias; they are unaccounted for variables that impact the response and may be related to the explanatory variables.
Bias in Sampling
- Nonresponse bias occurs when selected individuals don’t respond, potentially skewing results.
- Sampling bias favors certain population segments, leading to unrepresentative data.
Experiment Components
- A control group provides a baseline for comparing treatment effects.
- Blinding prevents participants or researchers from knowing treatment assignments, reducing potential bias.
- A placebo mimics the experimental medication but lacks therapeutic effects, ensuring comparison between treatment and control groups.
Studying That Suits You
Use AI to generate personalized quizzes and flashcards to suit your learning preferences.
Description
Test your knowledge with these flashcards covering key concepts from Math 133, Chapter 3. This chapter focuses on important principles of statistics and research methodologies, including double-blind experiments and sampling bias. Perfect for students looking to reinforce their understanding of statistical concepts.
