Experimental Design and ANOVA Quiz

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Questions and Answers

A psychologist wanted to examine the development of vocabulary skills for a group of 3-year-old children when they turn 4 and then again at age 5. What is this an example of?

  • One-way within-subjects design (correct)
  • One-way between-subjects design
  • Two-way between-subjects design
  • None of the above

A researcher was interested in studying student motivation in elementary school and the way it impacts final school average. The researcher also believed that enthusiasm for school was also related to final school average. At the end of the school year, a random sample of 20 students from fourth through sixth grade was selected, and measures were taken for all variables. The average scores were compared for each group. What is this an example of?

  • Two-way between-subjects design (correct)
  • One-way between-subjects design
  • One-way within-subjects design
  • None of the above

A researcher was interested in studying student motivation in elementary school. A sample of 20 students at the fourth-grade level were administered an inventory measuring motivation. Measures were taken at the beginning of the school year, at the midpoint, and again at the end of the school year. What design did this researcher use?

  • One-way within-subjects design (correct)
  • One-way between-subjects design
  • Two-way between-subjects design
  • None of the above

A researcher was interested in studying student motivation in elementary school and the way it impacts final school average across three different elementary levels. A sample of 20 students was randomly selected from fourth grade to sixth grade for motivation levels categorized as high, medium, and low. Measures were taken for motivation and final school average, and the average scores were compared across the groups. What is this an example of?

<p>Two-way between-subjects design (A)</p> Signup and view all the answers

At the .05 level of significance, what is the decision (reject or fail to reject) and conclusion in the context of this scenario?

<p>Reject the null hypothesis. There is sufficient evidence to indicate a difference in the average errors across the three different keyboard types. (D)</p> Signup and view all the answers

Approximately 60% of the variability in keyboard type can be explained by the errors made.

<p>True (A)</p> Signup and view all the answers

Based on the statistical results at the .05 level of significance, what is true?

<p>Participants using keyboard A did not have statistically less errors than keyboard B but did for keyboard C. (B)</p> Signup and view all the answers

Which of the following null and alternative hypotheses describe whether there are any differences in thinking or working proficiency for the humidity main effect?

<p>Ho: µlow = µhigh H1: µlow ≠ µhigh (A)</p> Signup and view all the answers

Which of the following null and alternative hypotheses describe whether there are any differences in thinking or working proficiency for the temperate main effect?

<p>Ho: µ70 = µ80 = µ90 Η1: µ70 ≠ µ80 ≠ µ90 (A)</p> Signup and view all the answers

Which of the following null and alternative hypotheses describe whether there are any differences in thinking or working proficiency for the interaction effect?

<p>Ho: µΤΧΗ = 0 Η1: µΤΧΗ≠ 0 (A)</p> Signup and view all the answers

Based on the graph below, we can conclude that the effect of room temperature on thinking or working proficiency most likely depends on the levels of humidity.

<p>True (A)</p> Signup and view all the answers

Based on the results above at the .05 level of significance, we can conclude that the effect of room temperature on thinking/working proficiency depends on the humidity level.

<p>True (A)</p> Signup and view all the answers

Based on the results above, approximately 27% of the variability in the average thinking or working proficiency score can be explained by room temperature.

<p>False (B)</p> Signup and view all the answers

Flashcards

Within-Subjects Design

A research design where the same participants are measured multiple times across different conditions or time points.

Between-Subjects Design

A research design where different groups of participants are assigned to different conditions or treatment groups.

Analysis of Variance (ANOVA)

A statistical test used to analyze the differences between means of two or more groups.

Main Effect

The effect of the independent variable on the dependent variable.

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Interaction Effect

The combined effect of two or more independent variables on the dependent variable.

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Alpha Level

The statistical significance level used to determine whether the null hypothesis is rejected.

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Post Hoc Test

A statistical test used to compare the differences between means after a significant ANOVA result.

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Eta-Squared

A measure of the effect size, indicating the proportion of variance explained by the independent variable.

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One-Way ANOVA

A research design studying the effects of one independent variable with two or more levels.

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Two-Way ANOVA

A research design studying the effects of two or more independent variables.

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Fail to Reject the Null Hypothesis

A scenario where the observed effect is likely due to chance, and the null hypothesis is not rejected.

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Reject the Null Hypothesis

A scenario where the observed effect is unlikely due to chance, and the null hypothesis is rejected.

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Null Hypothesis

The hypothesis claiming no significant difference between groups.

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P < Alpha

The observed effect is statistically significant, meaning it is unlikely to be due to chance alone.

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Vocabulary Development Study

A one-way within-subjects design measures vocabulary skills at different ages.

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Student Motivation and Enthusiasm Study

A two-way between-subjects design investigates student motivation and school enthusiasm on final grades.

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Student Motivation Over Time Study

A one-way within-subjects design measures student motivation at different points in the school year.

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Student Motivation and Grade Level Study

A two-way between-subjects design examines motivation and grade level on final grades.

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Keyboard Design Study

A one-way ANOVA is used to analyze the differences in typing errors across different keyboard designs.

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Conclusion of Keyboard Design Study

The ANOVA results show a significant difference in the average number of typing errors across the three keyboard designs, indicating that keyboard design does affect typing errors.

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Effect Size Interpretation

The eta-squared value of .60 indicates that approximately 60% of the variability in typing errors can be explained by the type of keyboard used.

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Post Hoc Results Interpretation

The post hoc tests indicate that there is a statistically significant difference in typing errors between Keyboard A and Keyboard C, but not between Keyboard A and Keyboard B, or Keyboard B and Keyboard C.

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Decision Rule

The null hypothesis is rejected when the p-value is less than the alpha level.

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Conclusion Based on P Value

The conclusion is that there is sufficient evidence to indicate a difference in the average number of errors across the three different keyboard types.

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Effect Size

A measure of the strength or magnitude of an effect.

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Within-Group Variance

The variation within each group.

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Between-Group Variance

The variation between different groups.

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Statistical Analysis

A statistical tool used to analyze data from experiments.

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Interpretation of Results

The process of drawing conclusions from statistical results.

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Variable Relationship

The concept of understanding the relationship between variables and how they influence each other.

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Study Notes

Quiz Details

  • This quiz assesses understanding of experimental design, ANOVA, hypothesis formulation, and effect size interpretation.
  • It includes research-based scenarios and multiple-choice questions.
  • The quiz consists of 14 multiple-choice questions.
  • Students have one attempt and a 60-minute time limit.
  • Review of assigned textbook and lecture materials is recommended.
  • Some questions require analyzing ANOVA results, interpreting post-hoc comparisons, or evaluating main and interaction effects.
  • Focus on applying theory to real-world examples.

Within-Subjects vs. Between-Subjects Designs

  • Within-subjects design: One group of subjects is measured multiple times.
  • Between-subjects design: Different groups of subjects are compared.
  • Example quiz questions illustrate the applications of these designs in scenarios.

ANOVA Analysis

  • ANOVA analysis: Used to analyze data from within-subjects and between-subjects designs concerning differences in group averages.
  • Descriptive statistics (means, standard deviations), ANOVA summary tables, and post-hoc tests interpretations are relevant to quiz questions.

Effect Sizes

  • Effect size: Measures the magnitude of the effect in research scenarios.
  • Example quiz questions incorporate interpretation of effect size data.

Research Examples

  • Quiz questions utilize scenarios from psychological research.
  • These scenarios emphasize problem-solving methodology including hypothesis testing, interpreting results.
  • Appropriate experimental design is related to each scenario.

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