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. (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 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 H1: 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: µTxH = 0 H1: µTxH≠ 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>False (B)</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 one group of participants is measured on a single dependent variable multiple times.

Between-Subjects Design

A research design where different groups of participants are measured on a single dependent variable, and the results are compared.

Analysis of Variance (ANOVA)

A statistical technique used to analyze differences between groups, particularly in within-subjects and between-subjects designs.

Two-Way Between-Subjects Design

A research design that includes two independent variables, allowing for examination of main effects (impact of each variable) and interaction effects (combined impact of both variables).

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Main Effect

The effect of one independent variable on the dependent variable, ignoring the influence of the other independent variable.

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Interaction Effect

The combined effect of two or more independent variables on the dependent variable, where their combined impact is different from their individual effects.

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Post-Hoc Test

A statistical test used to compare means between groups after ANOVA reveals a significant difference between groups. It helps determine which specific groups differ from each other.

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Effect Size

A measure of the strength of the relationship between variables, expressed as a proportion of variance in the dependent variable explained by the independent variable.

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Eta-Squared

A statistical value representing the proportion of variance in the dependent variable explained by the independent variable.

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P-Value

The probability value obtained from statistical tests like ANOVA, which indicates the likelihood of obtaining the observed results if there was no real effect in the population.

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Null Hypothesis

A hypothesis that states there is no effect or difference between groups or conditions being compared.

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Alternative Hypothesis

A hypothesis that states there is a significant effect or difference between groups or conditions being compared.

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Alpha Level

The level of significance used in hypothesis testing, typically set at 0.05. It represents the maximum acceptable risk of rejecting a true null hypothesis (Type I error).

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Statistical Decision

The decision to reject or fail to reject the null hypothesis based on the p-value and alpha level.

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Conclusion

An interpretation of the statistical results in the context of the research question or scenario.

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Type I Error

A type of error that occurs when you reject the null hypothesis when it is actually true.

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Type II Error

A type of error that occurs when you fail to reject the null hypothesis when it is actually false.

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One-Way Within-Subjects Design

A research design examining how a single independent variable affects a dependent variable by measuring the same group of participants repeatedly.

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One-Way Between-Subjects Design

A research design examining how a single independent variable with two or more levels affects a dependent variable, by comparing different groups of participants.

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Keyboard Design Experiment

An experiment that involves measuring the number of errors made by participants while typing on different keyboard designs.

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Mean

The average or typical value of a set of scores or measurements.

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Variance

The total variation or spread of scores around the mean in a dataset.

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Eta-Squared

A measure of the proportion of variance in the dependent variable that can be explained by the independent variable.

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Analysis of Variance (ANOVA)

A statistical test used to compare several groups to determine if their means are significantly different from each other.

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Post-Hoc Comparisons

The process of making specific comparisons between group means after a significant effect is found in an ANOVA test.

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Tukey's HSD Test

A type of post-hoc test used to compare the means of all possible pairs of groups, controlling for the overall Type I error rate.

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P-value

The value that represents the probability of observing the obtained results if there was no real effect or difference between groups.

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Type I Error

Rejecting the null hypothesis when it is actually true.

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Type II Error

Failing to reject the null hypothesis when it is actually false.

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Sample Size (N)

The number of participants or observations in a group or sample.

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Typing Errors

The number of errors made by participants while typing on a specific keyboard design.

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Study Notes

Quiz Details

  • This quiz assesses understanding of experimental design, ANOVA, and hypothesis formulation.
  • Includes scenarios and multiple-choice questions, testing interaction effects and drawing conclusions from statistical significance levels.
  • Instructions emphasize reviewing assigned materials.
  • Some questions involve analyzing ANOVA results and evaluating main/interaction effects.
  • Focus on applying theoretical knowledge to real-world examples.

Question 1

  • Description: Examines vocabulary development in 3-year-olds at ages 4 and 5.
  • Type: One-way within-subjects design.
  • Rationale: One group of subjects, measured multiple times on one dependent variable.

Question 2

  • Description: Studies student motivation and its impact on final school average at different grade levels.
  • Type: Two-way between-subjects design.
  • Rationale: Two factors (motivation, grade level) are compared across different groups.

Question 3

  • Description: Examines student motivation over time.
  • Type: One-way within-subjects design.
  • Rationale: One group of subjects measured multiple times on one dependent variable (motivation).
  • One variable measured across three time points by the same subjects.

Question 4

  • Description: Examines student motivation and average across elementary school levels.
  • Type: Two-way between subjects design
  • Rationale: Two factors (motivation, and grade level) are compared across different grade levels with random sampling.

Question 5

  • Description: Three different computer keyboard designs are studied (A, B, C).
  • Type: One-way between-subjects design
  • Rationale: Researchers compares performance on a task varying the keyboard. (A sample, and error measurement).

Question 6

  • Decision: Reject null hypothesis.
  • Reasoning: Sufficient evidence for a difference in average errors across the three keyboard types (p<alpha).

Question 7

  • Analysis: Analyzing the results of a one-way ANOVA design from a human factors study.

Question 8

  • Statement: Approximately 60% variability in keyboard errors can be explained by the type of keyboard.
  • Rationale: Interpretation of effect size (eta-squared).

Question 9

  • Analysis: Three different groups with different keyboards with a comparison of average errors in this analysis.
  • Result: Statistically significant difference in average errors between keyboard A and C only at the .05 level.

Question 10 

  • Analysis: Describes the hypotheses testing for differences in thinking and/or working proficiency for the humidity main effect.
  • Result: The hypothesis describes the difference in proficiency levels across various humidity levels.

Question 11

  • Analysis: Using Two-way ANOVA to consider interaction from a research study measuring thinking proficiency. 
  • Result: Testing whether the effect of room temperature on thinking performance varies depending on humidity levels.

Question 12

  • Analysis: Determine whether a significant difference exists in performance across different temperatures levels(T).
  • Hypothesis: Null and alternative hypotheses describe whether there differences across the temperature levels (T) based on research data for proficiency scores.

Question 13

  • Analysis: A study investigates the effects of temperature (T) and humidity (H) on thinking or working proficiency.
  • Hypothesis: Null and alternative hypotheses describing differences in proficiency based on temperature levels (T).

Question 14

  • Analysis: Determining if the effect of room temperature depends on the levels of humidity.
  • Result: True, as the lines on the graph are not parallel.

Question 15

  • Analysis: Determining if temperature effects on working proficiency differ based on humidity levels.
  • Result: True, there is an interaction, as presented in the graph the lines of different humidity levels are not parallel.

Question 16

  • Analysis: If approximately 27% of performance variability can be attributed to room temperature.
  • Result: True - Using partial-eta squared to calculate the proportion that can be explained and described from the provided ANOVA, (from the source document).

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