Haptic feedback and difficulty level. Example 13.2 (page 652) describes the setting for a two-way ANOVA design that compares different types of controllers and obstacle course difficulty levels. Give the degrees of freedom for each of the F statistics that are used to test the main effects and the interaction for this problem.
Added by Jennifer M.
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Step 1: Identify the factors and their levels In this two-way ANOVA design, we have two factors: - Factor A: Controller type (with different types of controllers) - Factor B: Obstacle course difficulty level (with different levels of difficulty) Show more…
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A group of technology students is interested in whether haptic feedback (forces and vibrations applied through a joystick) is helpful in navigating a simulated game environment they created. To investigate this, they randomly assign 20 students to each of three joystick controller types and record the time (seconds) it takes to complete a navigation mission. The joystick types are (1) a standard video game joystick, (2) a game joystick with force feedback, and (3) a game joystick with vibration feedback. Using the table below of group means and standard deviations, construct an ANOVA table (9 points, 1 per blank). Based on the F statistic and degrees of freedom, compute the p-value. What do you conclude (1 point)?
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A one-way independent ANOVA uses what type of design? between-subjects within-subjects single-sample In an ANOVA, the word "level" refers to: an independent variable the treatment conditions or groups on the IV The term "one-way" in an ANOVA refers to the fact that the design used has only one: treatment condition independent variable sample population a. when you have a significant F (there is a treatment effect) b. when you have more than two groups or treatment conditions on the independent variable c. you do not need to conduct post-hoc tests with a one-way independent ANOVA - those are reserved for two-way ANOVAs to determine if there is an interaction a and b The main advantage of a one-way independent ANOVA over a t-test is that you can compare more than two groups' means. True False
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