Investigating the interaction effect between different levels of response variable is one of the advantages in the two-factor factorial design.
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Q: An amusement park studied methods for decreasing the waiting time (minutes) for rides by loading and…
A: Given information: Type of Ride Roller Coaster Screaming Demaon Log Flume Method 1 41 52…
Q: An amusement park studied methods for decreasing the waiting time (minutes) for rides by loading and…
A: From the information, given thatLet Factor A denotes the method of loading and unloadingLet Factor B…
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Q: global research study found that the majority of today's working women would prefer a better…
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Q: An amusement park studied methods for decreasing the waiting time (minutes) for rides by loading and…
A: From the given information, Factor A – Method of loading or unloading Factor B – Type of ride…
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Q: An amusement park studied methods for decreasing the waiting time (minutes) for rides by loading and…
A: The data shows the type of ride and method of loading.
Q: An amusement park studied methods for decreasing the waiting time (minutes) for rides by loading and…
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Q: For two way ANOVA model, a significant interaction effect implies that both predictors(factors) have…
A: For two way ANOVA model, a significant interaction effect implies that both predictors(factors) have…
Q: An amusement park studied methods for decreasing the waiting time (minutes) for rides by loading and…
A: Note: Hi there! Thank you for posting the question. As the decimal places are not mentioned clearly,…
Q: An amusement park studied methods for decreasing the waiting time (minutes) for rides by loading and…
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A: In this case, it is obtained that there are significant main effects due to factor A and B.
Q: No VR Treatment (Control) VR Treatment n = 19 n = 23 M = 24 M = 21 SS = 210 SS = 184 d.)…
A: Summary of the data from the study is provided below. No VR Treatment (Control) VR Treatment…
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- The structure of a two-factor study can be presented as a matrix, with one factor determining the rows and the second factor determining the columns. With this structure in mind, identify the three separate hypothesis tests that make up a two-factor ANOVA, and explain the purpose of each test. Describe the mean differences that are evaluated by each of the three hypothesis test.Psychologists have identified 20 clients, 10 women and 10 men, and divided them into groups of five to determine the effect of matching the sex of the client and the sex of the therapist on the number of activities of daily living (ad1) performed by depressed clients. (a) Identify one of the independent variables. (b) Identify the other independent variable. (c) identify the dependent variable. (d) Using SPSS test all main and interaction effects at the .05 level of significance. Create a table including the cell means and marginal means and label each variable and level. State your null decision and conclusion (step 5 hypothesis testing) for all main and interaction effects. Label each effect clearly. Report in APA format the F statistics for all main and interaction effects. Be sure to report the best p-value possible.Q4 Deep leaming is a type of Machine Learning, inspired by the function and structure of a human brain, where machines can learn by experience and acquire skills without any human involvement. Table Q4 shows the relation of data amount and the performance of a deep learning technique capability to perform COVID-19 face mask identification among crowd in Pasar Rabu, Taman Universiti, Parit Raja. Table Q4 Independent variable Dependent variable Face mask identification Set of experiment Training data size, x аccuracy (%), у 1 100 30 200 40 3 300 50 400 55 500 60 6. 600 70 7 700 75 8 800 80 9 900 85 10 1000 90 10 10 10 Given > r; = 4600, = 635, > = 2860000 i=1 i=1 i=1 10 10 = 43875, >r yi = 322000 (a) Determine Sr, Syy, and Sry (b) Determine B. B. (c) Determine the estimated regression line equation.
- An amusement park studied methods for decreasing the waiting time (minutes) for rides by loading and unloading riders more efficiently. Two alternative loading/unloading methods have been proposed. To account for potential differences due to the type of ride and the possible interaction between the method of loading and unloading and the type of ride, a factorial experiment was designed. Use the following data to test for any significant effect due to the loading and unloading method, the type of ride, and interaction. Use a = 0.05. Factor A is method of loading and unloading; Factor B is the type of ride. Type of Ride Roller Coaster Screaming Demon Long Flume Method 1 49 50 47 51 42 43 Method 2 48 46 47 50 42 43 Set up the ANOVA table (to whole number, but p-value to 4 decimals and F value to 2 decimal, if necessary). Do not round intermediate calculations. Source of Variation Sum of Squares Degrees of Freedom Mean Square F p-value Factor A Factor B Interaction Error Total The p-value…Q3 explain THREE (3) major issues in handling Big Data. Q4 (a) Discuss the steps in the Data Life Cycle. List down any FOUR (4) important issues that required when designing a simulation study. (b)Let Factor A have three levels and Factor B have five levels. If the interaction between A and B is significant, what is the value of ? for the q-curve if we are performing Tukey’s multiple-comparison procedure to determine which treatment means are different?
- A researcher conducts a two-way ANOVA to determine how eating breakfast affects children's grades in school. Factor A has three levels: no breakfast, sugary breakfast, high protein breakfast. Factor B has two levels: males and females. Factor B has no main effect and there is no interaction effect. It is safe to conclude that _________. a. Factor A does not influence the participant's grades b. Factor B does not influence the participant's grades c. Factor A has an influence on the participant's grades d. Factor B has an influence on the participant's grades Clear my choiceThe personality characteristics of business leaders (e.g., CEOS) are related to the operations of the businesses that they lead (Oreg & Berson, 2018). Traits like openness to experience are related to positive financial outcomes and other traits are related to negative financial outcomes for their businesses. Suppose that a board of directors is interested in evaluating the personality of their leadership. Among a sample of n = 16 managers, the sample mean of the openness to experiences dimension of personality was M = 4.50. Assuming that u = 4.24 and o = 1.05 (Cobb-Clark & Schurer, 2012), use a two-tailed hypothesis test with a = .05 to test the hypothesis that this company's business leaders' openness to experience is different from the population. Standard Normal Distribution Mean - 0.0 Standard Deviation 1.0 .7198 .1401 .1401 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 -1.08 1.08 Step 1. Ho: ; H;: a = .05. Step 2. The critical region consists of Step 3. For these data the standard error is and…a) What is the strongest independent variable for the model predicting self-control for respondents living in good neighborhoods? and living in bad neighborhoods? b) In every situation above, the standard errors for the model predicting self-control for respondents in good neighborhoods are lower than the standard errors predicting self-control for respondents in bad neighborhoods. What might be one reason why this might occur?
- An amusement park studied methods for decreasing the waiting time (minutes) for rides by loading and unloading riders more efficiently. Two alternative loading/unloading methods have been proposed. To account for potential differences due to the type of ride and the possible interaction between the method of loading and unloading and the type of ride, a factorial experiment was designed. Use the following data to test for any significant effect due to the loading and unloading method, the type of ride, and interaction, Use a = ,05. Factor A is method of loading and unloading; Factor B is the type of ride. Type of Ride Roller Coaster Screaming Demon Long Flume Method 1 48 56 51 50 48 47 Method 2 51 55 52 53 51 48 a. Set up the ANOVA table (to 2 decimal, if necessary). Round p-value to four decimal places. Source of Variation Sum of Squares Degrees of Freedom Mean Square p-value Factor A Factor B Interaction Error TotalAn amusement park studied methods for decreasing the waiting time (minutes) for rides by loading and unloading riders more efficiently. Two alternative loading/unloading methods have been proposed. To account for potential differences due to the type of ride and the possible interaction between the method of loading and unloading and the type of ride, a factorial experiment was designed. Use the following data to test for any significant effect due to the loading and unloading method, the type of ride, and interaction. Use a=0.05 . Factor A is method of loading and unloading; Factor B is the type of ride. Type of Ride Roller Coaster Screaming Demon Long Flume Method 1 47 51 54 49 43 50 Method 2 51 47 50 53 43 46 Set up the ANOVA table (to whole number, but -value to 2 decimals and value to 1 decimal, if necessary). Source of Variation Sum of Squares Degrees of Freedom Mean Square F -value Factor A Factor B Interaction…Mr. Saif has conducted a research study to know the attitude of graduate students towards entrepreneurship business. In this regard, he has collected the data from the Sultan Qaboos University, Muscat and University of Technology and Applied Sciences, Muscat using a structured questionnaire. The feedback of 400 students has been collected from these universities. For the data analysis, the researcher has used exploratory factor analysis and regression to evaluate the factors influencing the attitude of students towards entrepreneurship business. Question: Evaluate the methodology approach used for this study by discussing its features.