 The first video game device was called the Cathode Ray Tube Amusement Device, which was created in 1947  The first game console that was available was developed in 1972, called the Magnavox Odyssey  The first console to use CDs to play games was the Sony Playstation, which was released in 1994  The Playstation 2 is the most popular video game console, selling over 140 million worldwide  Pokemon Red and Blue editions are the highest selling games to date, selling over 20 million copies worldwide (These are non-bundled games)  Video game consoles have now evolved to have 3D capabilities, motion-tracking software, and realistic graphics

 What we really wanted to find out with this collection was the habits of gamers, like: › Does the amount of games owned affect how much the subject plays? › Is there a relationship between how frequent a person visits a game store and how much they play? › Does age affect how much a person plays? › Are purchases at video game stores independent of how frequent the store is visited? › Do people who favor a certain genre of game play more?

 To collect the necessary data to analyze, we had to stake out various game stores and interviewed every other person who walked out the door

 Our main quantitative data  Units: Hours  Mean: hrs  Standard deviation: hrs  Range: › IQR = 12hrs › 5 hrs – 30 hrs = 25 hrs

 Data is right skewed  Normal probability plot is curved in the beginning and in the end, but is overall normal

 Is their a relationship between these two values?  Scatter plot is: › Moderate Scattered › Linear › Positive  Equation: ›.515(#_OF_GAMES) + 25 = HRS_PER_WEEK  Correlation =.6305  R 2 =.40  40% of the change in hours played per week can be seen from the change in the number of games a person owns

 What is the relationship between the player’s age and how many hours a week the player plays?  Scatter plot is: › Weak › Negative › Linear › Not scattered  Equation: › -.183(HRS_PER_WEEK) + 18 = AGE  Correlation =.228  R 2 =.052  5.2% of the change in player’s age can be seen by the change in the hours played per week

 More infrequent visitors than frequent visitors  For both the frequent and infrequent visitors, the most common purchase was a game (go figure)

 Frequent: › Mean = › SD = 7.9  Infrequent: › Mean = › SD = 7.57

Frequent: 95% confident Frequent: State SRS Population > 10n n > 30 or normal probability plot Check Data collected Randomly All people who frequent game stores > > 30 Conditions met  Students t distribution  1-sample t-interval We are 95% confident that the true value of hours that people play video games that frequently go to games stores is between hours and hours

Infrequent: 95% Confident Infrequent: State SRS Population > 10n n > 30 or normal probability plot Check Data collected Randomly All people who frequent game stores > > 30 NOT!! Conditions met  Students t distribution  1-sample t-interval There is an insufficient sample size but we will continue anyway We are 95% confident that the true value of hours that people play video games that frequently go to games stores is between hours and hours

State Independent SRS Pop1 > 10n1 Pop2 > 10n2 Both Populations are normal or > 30 Check Data sampled are independent SRS All who go to game stores frequently > 330 All who go to game stores infrequently > > > 30 NO!! Conditions met  Students t distribution  2-sample t-interval There is an insufficient sample size but we will continue anyway

95% confident We are 95% confident that the difference in hours between people who frequent game stores and those who done is between hours and hours

State Data are counts Population > 10n Data are independent All expected counts > 5 Check Categorical data All gamers > 470 SRS 3 of 8 cells have expected counts less than 5, but we are going to continue anyways There is no association between frequency and purchase There is an association between frequency and purchase Conditions met  x 2 distribution  X 2 test of independence

We fail to reject our Ho because the P-value of.69 is greater than the alpha of.05 We have sufficient evidence to say that there is no association between the frequency that you visit a store and what is purchased at the store

 The two most popular game genres are sports and shooting games  Sports: › Median = 10 › Small spread  Shooting: › Median = 16 › Large spread

State Independent SRS Pop1 > 10n1 Pop2 > 10n2 Both Populations are normal or > 30 Check Data sampled are independent SRS All who favor shooting > 130 All who favor sports > 90 Populations assumed normal We fail to reject our Ho because the P-value of is greater than the alpha of.05 We have sufficient evidence than there is no significant difference in the number of hours that people who favor shooting games opposed to sport games Conditions met  Students t distribution  2-sample t-test

 Observations show that the more games one owns the more games are owned, the more hours are played  No association between age and hours played  People most commonly buy a game when at the game store  People who frequently go to game stores play between hours and hours  People who infrequently go to game stores play between hours and hours  The average difference between people to frequently and infrequently go to game stores is between hours and hours

 There is no association between the frequency that you visit a store and what is purchased at the store  Than there is no significant difference in the number of hours that people who favor shooting games opposed to sport games

 Difference in collection  Events or deals  Times of the day  Holidays (memorial day)  People can lie  People blew us off  Our enthusiasm

 Very difficult to collect data in the short time due to low amount of people walking in  Our data seems to follow what we expected to see › Age and hours graph doesn’t