Unit 0 Quiz Study Guide: Experimental Design and Statistics

Unit 0 Quiz Study Guide

Experimental Design and Statistics Vocabulary

  • Quantitative data: Numerical information that can be measured and recorded.

  • Qualitative data: Non-numerical information that describes qualities or characteristics.

  • Inductive reasoning: Making generalizations based on specific observations.

  • Deductive reasoning: Drawing specific conclusions from general principles.

  • Hypothesis: A testable prediction about the relationship between variables.

  • Scientific law: A statement based on repeated experimental observations that describe some aspects of the universe.

  • Theory: A well-substantiated explanation acquired through the scientific method and repeatedly tested and confirmed.

  • Null hypothesis: A statement that there is no effect or no difference, serves as the default or starting assumption.

  • Alternative hypothesis: The statement that contradicts the null hypothesis, indicating the presence of an effect or a difference.

  • Variables: Elements that can change or be controlled in an experiment.
      - Independent variable: The variable that is deliberately manipulated.
      - Dependent variable: The variable that is measured or observed in response to the independent variable.

  • Constants: Conditions that remain unchanged throughout an experiment.

  • Controls: Baseline measurements or groups in an experiment that are not exposed to the independent variable.

  • Mean: The average value of a data set, calculated by summing all values and dividing by the number of values.

  • Median: The middle value in a data set when the numbers are arranged in order.

  • Mode: The value that appears most frequently in a data set.

  • Standard deviation (s): A measure of the amount of variation or dispersion in a set of values.

  • Standard error of the mean (SEM): The standard deviation divided by the square root of the sample size; it estimates how far the sample mean is likely to be from the true population mean.

  • Bar graph and error bars: Visual representations of data; error bars indicate the variability or potential error in measurements.

  • Chi-square: A statistical test used to determine if there is a significant difference between expected and observed frequencies in categorical data.

Key Skills

  • Given a description of an experiment, be able to construct both a null and alternative hypothesis.

  • Identify independent and dependent variables in an experimental scenario.

  • Determine the appropriate axis (x or y) for plotting each type of variable.

  • Explain the purpose of the null hypothesis: it provides a baseline to compare the effect of the independent variable.

  • Explain the purpose of controls: to eliminate alternative explanations and isolate the effect of the independent variable.

  • Perform calculations for mean, standard deviation, and standard error of the mean based on provided data.

  • Interpret meanings of standard deviation—low indicates low variability, while high indicates high variability.

  • Recognize that approximately 68% of data falls within 1 standard deviation of the mean, while about 95% falls within 2 standard deviations.

  • Create graphs that include appropriate labels, titles, scales, and error bars (using +/- 2 SEM).

  • Draw conclusions from statistical analyses of data sets.

  • Execute Chi Square analysis to evaluate whether to reject the null hypothesis based on data.

The following equations and formulas regarding statistical analysis will be provided on the quiz and AP exam.