A research group was interested if time spent in electronically simulated sport

Question

A research group was interested if time spent in electronically simulated sport activities (in semi-virtual, or enhanced reality) would have an improvement in reaction time in certain sport skills. Volunteers were required to spend at least 40 total minutes ‘practicing’ in electronic/virtual settings, but there was no limit to how long they could spend in the simulator. Training time was collected in several visits and participants were able to play as long as they wanted in each visit. Gender was recorded 1=female, 2=male. Life stage was collected in 4 categories: 1=young independent-pre children, 2=young families (with children, but any child younger than 10), 3=mid-age with all kids older than 10, 4=mid-latter age with all kids out of the home. For the sake of this analysis, any person not meeting these descriptors (older unmarried or no kids in the home) are not included in the data. Reaction time is a score from a test of several sport skills and was collected prior to the simulated sport activities and again at the end of the program. Additionally, program satisfaction scores were collected after the program (collected on a 1=’not at all satisfied’ to 9=’extremely satisfied’ Likert-type scale). It is very likely that you might have to compute or recode new variables to answer all of these questions. Your task is to address each of the research questions below (1-10) by responding to each these discussion points (a-d) What variables will be used, what type of measurement for each variable (nominal, ordinal, interval, ratio)? What test should be used to answer the question? Discuss/justify with specific reasons. CLEARLY state both null and alternative hypotheses using variable names. Fully discuss the results with insights into what the results mean in practical application language.

10. RESEARCH QUESTIONS

1.Did males voluntarily spend more time in the simulator than women?

2.Does life situation/stage impact the time voluntarily spent in the simulator?

3.Is there a difference in program satisfaction between males and females?

4.Is there a difference in program satisfaction in each life stage?

5.Does total minutes spent in simulated practice predict if a participant improves their reaction time (yes vs. no)?

6.Is there an additional effect of both gender and life stage on the time spent in simulated practice?

7.Does program satisfaction predict the amount of time spent in simulated practice?

8.Is a person’s improvement score (pre score – post score) predicted by time spent in in simulated practice?

9.Is the difference in time spent in the simulator by life stage effected by (controlled for) program satisfaction?

10.Overall, is the program effective in improving reaction time? I do not need anyone to do this for me.

I am hoping someone can explain which tests I need to run on spss for the 10 questions and why. I can do the work myself. I just need some help understanding what tests to run and why for each question. I would appreciate the guidance. Thanks

BM SPSS Statistics Data Editor FinalProjectData (1).sav [DataS le Edit View Data Iransform Analyze Graphs Utilities Extensions Window Help Role Input Columns 12 12 12 17 17 12 12 Ali Right Right Right Right Right Right Right Ordinal?Input Measure Scale Nominal Nominal?Input Scale Scale Scale Label Values Missi WidthDecimals 12 12 12 17 17 12 Name None None None None None None None ID number DnumberNumeric Numeric life stage Numeric1 Reaction_pre Numeric Reaction_P Numeric minutes trai.. Numeric program sa... Numeric 2 gender Input Input Input 10 12 13 14 15 16 18 19 20

Explanation / Answer

The following test can be used for each of the question numbered as follows:

1. A t-test for two independent samples can be used to compare the time males voluntarily spent in the simulator to the time females voluntarily spent in the simulator; because this test will help you campare the average times the two genders are spending in the simulator and draw a relevant conclusion.

2. A One-Way ANOVA analysis can be done between the situation/stage in life and the voluntary time spent in the simulator. This will help you understand if the 'factor' Stage in life has a significant effect on the voluntary time spent in the incubator. If a sifnificance is found in the ANOVA analysis then a further analysis can be done to identify the means that differ significantly.

3. A t-test for two independent samples can be used to compare the program satisfaction level between the two genders. This test will help you campare the program satisfaction level in the two genders and draw a relevant conclusion.

4. A One-Way ANOVA analysis can be done to check if the factor "Stage in life" has a significant effect on the satisfaction level from the program. If a significant difference is found between the factors then a futher analysis can be performed to check satisfaction levels for which stages in lefe differ significantly.

5. A Correlation Analysis can be performed between the time spent in simulated practice and the reaction time. A significant positive correlation will suggest that there is a strong relation between two measures.

6. A Two-Way ANOVA can be performed to check if there is an additional effect of both gender and life stage on the time spent in simulated practice. Interaction efffect can be studied to check it there is association between gender and stage in life on the effect on time spent in simulated practice.

7. A Correlation Analysis can be performed between the time spent in smiulated practice and the program satisfaction. A significant positive correlation will suggest that there is a strong relation between two measures.

8. A Correlation Analysis can be performed between the score of a person and the time spent in in simulated practice. A significant correlation will indicate that a person’s improvement score can be predicted by time spent in in simulated practice.

9. An ANOVA Analysis can be done to check for the significant effects on time spent in the simulator by life stage effected by (controlled for) program satisfaction.

10. A t-test for difference in dependent samples can be done to make a comparison between the reaction time before and after the program. The test will help identify if there was a significant improvement in the reaction time after the program.

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