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A collection of vocabulary flashcards focused on key terms and definitions pertinent to K300 Exam I preparation.
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Simulations
Interactive models that allow users to experiment with variables and see outcomes, such as coin-sampling and match-sampling.
Classifying Variables
The process of categorizing variables as continuous, discrete, nominal, or ordinal.
Independent Variables
Variables that are manipulated in an experiment to observe their effect on dependent variables.
Dependent Variables
Variables that are measured in an experiment to assess the impact of independent variables.
Confounds
Extraneous variables that may influence the results of an experiment.
Sample Size
The number of observations or replicates used in a statistical sample, which affects the validity of results.
Histogram
A graphical representation showing the distribution of numerical data.
Measures of Central Tendency
Statistics that describe the center of a dataset, including mean, median, and mode.
Variability
The extent to which data points differ from each other in a dataset.
Standard Deviation
A measure of the amount of variation or dispersion in a set of values.
Z Score
a measure of how many standard deviations a particular score is above or below the mean of its distribution
Raw Score
The original value or measurement before any transformation.
Standard Error
The standard deviation of the sampling distribution of a statistic.
Sampling Distribution
A probability distribution of a statistic obtained through a large number of samples drawn from a specific population.
Normal Distribution
A bell-shaped distribution where most observations cluster around the central peak.
Bar Chart
A graph that represents data with rectangular bars representing different values.
Line Graph
A type of chart that displays information as a series of data points connected by straight line segments.
Box and Whisker Chart
A graphical representation that summarizes data based on a five-number summary: minimum, first quartile, median, third quartile, and maximum.
Model
A simplified representation of reality used to explain or predict phenomena.
Null Hypothesis
A statement asserting that there is no effect or no difference, serving as a starting point for statistical testing.
Rejecting the Null Hypothesis
Concluding that there is sufficient evidence to suggest a meaningful effect or difference in the data.
p Value
A measure that helps determine the statistical significance of results in hypothesis testing.
Alpha Level
The threshold for determining statistical significance, commonly set at 0.05.
Type I Error
Incorrectly rejecting a true null hypothesis.
Type II Error
Failing to reject a false null hypothesis.
Base Rates
The natural frequency of a condition or characteristic in a given population, important for interpreting statistical claims.
Relative Statistic
A statistic that compares values in relation to one another.
Absolute Statistic
A statistic that provides raw data without reference to other values.
Excel Skills
Essential competencies in using Excel for data management and statistical analysis.
Simulation Applet
An online tool used to model experiments and visualize results in a simulated environment.
Hypothesis Testing
A method of making statistical inferences about population parameters based on sample data.
Continuous Variable
A variable that can take any value within a given range, typically measured (e.g., height, temperature).
Discrete Variable
A variable that can only take on-specific, distinct values, usually counted (e.g., number of children, dice roll).
Nominal Variable
A categorical variable without any natural order or ranking (e.g., gender, eye color).
Ordinal Variable
A categorical variable with a clear order or ranking among categories, but the differences between categories are not necessarily equal (e.g., education level (high school, college, grad school), satisfaction rating (poor, fair, good)).