Questions and Answers
What does 'population' refer to in statistics?
What is a sample in research?
What is sampling error?
The amount of error associated with a sample due to its deviation from the population.
Define descriptive statistics.
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What are inferential statistics?
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What does an empirical research study involve?
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What is an independent variable?
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What are variables in statistics?
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What is a dependent variable?
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Define operational definition.
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What is a construct in research?
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What does a theory consist of?
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What is a research hypothesis?
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What is a statistic?
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What is a parameter?
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What is a null hypothesis?
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What is a discrete variable?
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What is a continuous variable?
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Define nominal-level variable.
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What is an ordinal-level variable?
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Define interval-level variable.
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What is a ratio-level variable?
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What is a histogram?
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What is a bar graph?
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What does a frequency table do?
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What does mean refer to in statistics?
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What is median in statistics?
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Define mode in statistics.
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What is a weighted mean?
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What are measures of central tendency?
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Study Notes
Statistical Definitions
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Population: The comprehensive group of individuals or entities from which a sample may be drawn for a research study, essential for making statistical inferences.
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Sample: A selected subset of the population representing that group, crucial for avoiding bias during research observations.
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Sampling Error: The degree of discrepancy between a sample statistic and the population parameter, often due to random sampling variability.
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Descriptive Statistics: Techniques used to summarize and describe data through measures of central tendency, dispersion, and visual representations.
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Inferential Statistics: Methods that enable conclusions to be made about a population based on sample data, focused on establishing relationships or differences between variables.
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Empirical Research Study: A study grounded in observation and measurement, relying on experimental methods to derive conclusions.
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Independent Variable: The variable in an experiment that is manipulated to observe its effect on the dependent variable.
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Variables: Quantitative elements in research that can change and affect outcomes.
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Dependent Variable: The outcome variable that is observed for changes in response to variations in the independent variable.
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Operational Definition: Clear description of how variables are measured or defined in a study, enabling replicability and clarity.
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Construct: An abstract idea formulated from specific instances, often guiding research questions and hypotheses.
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Theory: A structured framework of knowledge within a particular domain, supported by empirical findings and interpretations.
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Research Hypothesis: A specific, testable prediction about the relationship or direction between variables.
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Statistic: A numerical representation reflecting a specific attribute of a sample.
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Parameter: A characteristic value (like mean or variance) that describes an entire population, estimable from sample data.
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Null Hypothesis: A proposition stating there is no significant difference or relationship between observed data sets.
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Discrete Variable: A variable that can only take on specific, countable values.
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Continuous Variable: A variable that can have an infinite number of values within a given range, such as age or height.
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Nominal-Level Variable: A categorical variable that represents distinct groups without a specific order.
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Ordinal-Level Variable: A categorical variable that features an inherent order or ranking among the categories.
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Interval-Level Variable: A continuous variable that maintains equal intervals between values but lacks a true zero point.
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Ratio-Level Variable: A continuous variable with a true zero point, allowing for the calculation of ratios.
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Histogram: A graphical representation showing frequency distribution across equally divided intervals.
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Bar Graph: A visual tool depicting category comparisons via the lengths of bars.
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Frequency Table: A tabulated representation showcasing the occurrence of different values or categories.
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Mean: The average value computed by summing all observations and dividing by the count.
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Median: The middle value when a data set is organized in ascending or descending order.
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Mode: The value that appears most frequently in a data set.
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Weighted Mean: An average where each value is multiplied by its importance before calculating the overall mean.
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Measures of Central Tendency: Statistical metrics that capture the center point of a data set, primarily mean, median, and mode.
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Measures of Variability: Statistical indicators that describe the spread or dispersion within a data set, further enhancing the understanding of data characteristics.
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Test your knowledge with these flashcards covering essential definitions in statistics. Whether it's about populations, samples, or statistical inferences, these cards will enhance your understanding of statistical concepts. Perfect for students and professionals alike!