i need help for this question please.

a options: A one way ANOVA / A two way 2 X 4 ANOVA / A two-way 3 X 4 ANOVA / A two-way 3 X 2 ANOVA

b options: Reject the null hypothesis / Retain the null hypothesis

c options: Yes, follow-up analysis is needed / No, follow-up analysis is not needed

Along with ques d / e / f

Scenario: A novel experiment with 208 participants was run by a psychology grad student at Concordia. The experiment examined mean visual search efficiency (response time) of the famous "Where's Waldo?" task as a function of the two factors: type of location (i.e., city, rural, boat, amusement park), and dominant gender present in picture (i.e., female, male, not indicated). Participants were given a maximum of 120 seconds to find Waldo in one picture. Response times for finding Waldo were recorded for each trial. The response times are summarized separately by condition with respect to the two factors in the following figure. The researcher is interested in analyzing the differences in mean response time between locations and present gender. 120 - 100 gender male Y 80- female not indicated City Rural Boat Amusement Park location a. What type of analysis should the grad student use to analyse these data? b. According to the statistics shown in the summary output below, would you retain or reject the null hypothesis of no difference between means of conditions? . Would you need to perform any follow-up tests to arrive at a definitive statement about differences in means? d. Please explain the reasons for your decision. e. What is the number of degrees of freedom that are attributed to the individual error in this analysis? f.What is the number of degrees of freedom that are attributed to all levels of the independent variables but not participants themselves in this model? Df Sum Sq Mean Sq F value Pr(>F) ## location 3 1 0.5 0.001 1.060 ## gender 2 535 267.3 0. 491 0.613 ## Residuals 202 109933 544.2 d. The brief reasons for my decision are: e. Number of degrees of freedom that are attributed to the individual error in this analysis: f. Number of degrees of freedom that are attributed to all levels of the independent variables but not participants themselves in this model