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Group 2 Term Project

Group 2 Term Project. Heaven Kummer, Curtis Bryant, Bonni Patterson, Amy Evans. Research Question. “For adult men, is age related to hours of video games played per week?”.

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Group 2 Term Project

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  1. Group 2 Term Project Heaven Kummer, Curtis Bryant, Bonni Patterson, Amy Evans

  2. Research Question “For adult men, is age related to hours of video games played per week?”

  3. The purpose of thisstudy is to determine if for adult men, is age related to hours of video games played per week. We successfully completed our study by using systematic sampling. We surveyed males above and including the age of 18 at local grocery stores, malls, and libraries. We set k=5 after the first 2 males we saw, until we reached our goal of surveying 200 men. We had six people in our group so each person surveyed 33-34 people to hit our 200 goal. We asked each male his age and hours spent playing video games per week.

  4. Our Group Data A=Male AgeB=Hours Played/Week

  5. Variable Comparison Age Summary Mode : 20 Outliers: 75,81 Hours Played Summary Mode: 0 Outliers: 22,25,27,28,30,40,50,100

  6. Frequency histograms Age of Males: Hours spent playing video games per week:

  7. Boxplots

  8. Scatterplot

  9. Distribution Analysis Our sample data had a fairly large distribution of age with a minimum of18 and maximum of 81 year old men. 50% of the men were from 18 to 27 years old. Only 12.5% of the men in the sample are over 50 years old. There are considerably more young men than old men in our sample. The distribution of hours of games played per week also had a large distribution with the minimum number of hours played at 0 hours and maximum hours played at 100 hours. Just over 25% of the men played 0hours per week or no video games at all. 57.5% of the men played between1 and 10 hours per week. We also can see a few extremes in our sample.One individual played on average 100 hours a week and two others respectively played on average 40 and 50 hours a week. These fewextremes make up only 1.5% of our sample data altogether. Therefore, according to our sample distribution, most adult men that doplay video games are between ages 18 and 27 and are young. And also according to our sample distribution most men that do play video games donot play very much, only playing 1 to 10 hours per week. So from our sample distribution we can see that on average, even young men who do play video games, do not play more than 10 hours of video games per week

  10. Linear Correlation Coefficient Correlation -The variables age and hours of games played per week are related inversely or have a negative linear relationship. As age risesthe hours of games played decreases. Our statistics show us that the linear correlation coefficient R = -0.288 and the absolute value of R or |R| = 0.288. The critical value for our sample size of 200 with95% confidence is 0.195. The linear correlation coefficient is greater than the critical value for our sample.(R>CV) or (0.288>0.195)Therefore, because the absolute value of R is higher than thecritical value at the 0.05 level of significance, we are 95% confidentthat there is a correlation between the two variables in thepopulation.

  11. Difficulties & Surprises • A difficulty we came across was trusting our data since there is such a skewed graph for our “ages” variable. • Another difficulty, which groups usually experience, was getting everyone to contribute their data towards the end of the semester. Starting with being assigned 8 members, we only ever heard from 6. And for the final presentation dwindled to 4 members. • Surprised to find out that some people actually spend 50 to 100 hours playing video games per WEEK!

  12. Interpretation & Conclusion Based on the histograms and boxplots both sets of data are skewed right. The scatterplot shows a clear correlation between gaming a lot and youth; as well as gaming a smaller amount and being older. Since there are outliers there was a worry that this wouldn’t be an accurate reflection for the population but the critical value and the sample size prove that they are normally distributed and provide an accurate reflection. If repeating this survey we would only include the data from Utah, because the data one of our group members got from Japan could be seen as a lurking variable. We would also include another location to try to increase our number of older subjects or switch our survey technique to one that would allow us to set the ages to be equal for young and old. For our research question: “For adult males, is age related to amount of time they spend playing video games per week?” There is sufficient information to conclude that there is a relationship between the age of males and the amount of hours they spend playing video games. They tend to play the most around the age of 20, and the amount on average decreases once they reach the age of approximately 29

  13. Contributions • Amy Evans: Purpose/Study design • Bonni Patterson: Group data & statistics for both variables. • Heaven Kummer: Histograms, boxplots, scatterplot including line of regression w/equation, surprises/difficulties, interpretation/conclusion , research question slide, title slide, contributions, & formatting powerpoints. • Curtis Bryant: Distribution analysis & linear correlation coefficient slide. Spring 2013 Statistics Francis McGrade

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