StatCrunch logo (home)

Report Properties
Thumbnail:
Owner: pdugger76
Created: Jun 13, 2019
Share: yes
Views: 85
 
Results in this report
 
Data sets in this report
None
 
Need help?
To copy selected text, right click to Copy or choose the Copy option under your browser's Edit menu. Text copied in this manner can be pasted directly into most documents with formatting maintained.
To copy selected graphs, right click on the graph to Copy. When pasting into a document, make sure to paste the graph content rather than a link to the graph. For example, to paste in MS Word choose Edit > Paste Special, and select the Device Independent Bitmap option.
You can now also Mail results and reports. The email may contain a simple link to the StatCrunch site or the complete output with data and graphics attached. In addition to being a great way to deliver output to someone else, this is also a great way to save your own hard copy. To try it out, simply click on the Mail link.
Video Game Survey Data Project Report
Mail   Print   Twitter   Facebook

Introduction

The purpose of the survey designed by group two (2) was to examine the habits related to cellular phone video game usage of the average American.  The population that the group members were able to obtain a sample from consisted of family, friends, and co-workers with ages ranging from thirteen (13) to ninety-eight (98).  Collection of survey data was obtained in person and by utilizing social media platforms (i.e., Facebook) – a convenience sample.  All responses were given on a voluntary basis and all respondent’s identifying information was held confidential.  The following questions were included in our survey:

1.Do you play video games on your cell phone? Circle one: yes no

2.What type of game do you usually play? Select one category: 

      Action/Adventure 

      Puzzle

      Role-Playing

      Sports

      Strategy

      Other

      I do not play video games on my phone.

3.How many hours a week do you spend playing video games on your cell phone?

4.What is your age in years?

Looking at a Categorical Variable

The pie chart that follows represents the responses for the multiple categorical survey question “What type of game do you usually play?” 

Result 1: Pie Chart of Video Games Played by Category   [Info]
Right click to copy

According to the visual representation in the pie graph and data, the mass of the survey respondents do not play video games on their cellphone (33.33%) followed closely by the puzzle category (32.52%).  The “other” category was the next highest with 9.76% of respondents.  There was a three-way tie (7.32%) among the action/adventure, strategy, and sports categories.  The least popular type of video game category among the survey respondents was role-playing (2.44%).

In order to see if there was a difference between the two categories, “does not play” and those that do engage in playing cellular phone games, the bar plot can be examined below for further insight. 

Result 2: Bar Plot of Gamers (All-Categories) Versus Non-Gamers   [Info]
Right click to copy

After examining the bar plot, the combined number of responses of those who play video games on their cellular device are greater than the total of those respondents that “do not play”.  While the “do not play” category was the highest response when evaluated by individual category (33.33%), it is almost 50% less than the overall total when the game types of those who do play are combined.

Looking at a Numerical Variable

The following histogram, boxplot, and summary statistics highlight the data for the survey question regarding “How many hours a week do you spend playing video games on your cell phone?”

Result 3: Histogram of Hours of Game Engagement per Week   [Info]
Right click to copy

Result 4: Boxplot of Game Engagement per Week   [Info]
Right click to copy

Result 5: Summary Stats of Game Engagement per Week   [Info]

Summary statistics:


ColumnnMeanVarianceStd. dev.Std. err.MedianRangeMinMaxQ1Q3ModeIQR
Hrs. per wk1234.719512239.348966.2728750.565606092300300707

The histogram, represented in Result 3, is skewed to the right or positively skewed.  “Distributions skewed to the right are more common…because it’s often easier to get exceptionally large values than values that are exceptionally small” (Triola, 2015, pp. 56-57).  The survey examined the respondent’s hours of engaging in cellphone game play and the lowest value that could be reported was zero (0) hours, which supports why the representation was common it its presentation.  There are also two (2) breaks in the data where there was no response for hours played (17.5-19 and 27.5-29 hours per week).

The mass of the responses fell within the 0-7 hours per week.  This range represents the modal class of the survey data.
 
The median is the best descriptor when analyzing the current video game data and results because of the distribution’s shape being positively skewed.
 
The mean of the data is 4.7 hours.  The midrange, (0 + 30)/2, is noted as 15 hours.  After comparing the midrange with the histogram representation, 15 hours does not seem like a viable measure of center.
The range is noted as 30 hours with a standard deviation of 6.3 hours.  The IQR of the data is 7, which is close in comparison when you calculate the data using the range rule of thumb (range/4 = 7.5) – a good approximation of the standard deviation.
 
There are five (5) outliers present, which are represented in the box plot (Result 4): 20, 22, 24, 25, and 30.  I have determined that while the outliers far exceed the average of 7.0 hours of game engagement per week, it is feasible that some individuals who are more dedicated to game play may easily achieve 20-30 hours of activity per week.  Thus, the outliers would not be considered erroneous in this case.  
 
Looking for a Relationship between Two Numerical Variables

The scatter plot assists in evaluating the data to determine if there is a correlation between the two (2) numerical survey questions: “How many hours a week do you spend playing video games on your cell phone?” and “What is your age in years?”
 

Result 6: Scatter Plot, Option 2   [Info]
Right click to copy

 
The result of the scatter plot shows no correlation or relationship as the visual data “[does] not show any obvious pattern…” (Triola, 2015, p. 61).  There are two (2) outliers, 30 hours and 98 age in years, represented in the scatter plot.  According to Triola (2015), the outliers are important to identify because their effects “can be substantial” to your data analysis (p. 120).  In this case, the outliers do not seem to have any impact as there is no correlation between cellphone video game habits and age.
 
The correlation coefficient for the paired data is 0.113, which is shown in Result 7 below.
 

Result 7: Correlation of game engagement hours/age   [Info]
Correlation between Hrs. per wk and Age is:
0.11290067

 
The absolute value of r is less than .196 (Table A-5, Critical Values of the Pearson Correlation Coefficient r), which supports that there is no statistical correlation between the hours of game play on a cellphone and the respondent’s age.  The lack of correlation supports and confirms the findings from scatter plot (Result 6) above.
 
References
 
Cassella, D. (2010, January 20). Video games: The state of play in 2010 [Image]. Digital Trends. Retrieved from https://www.digitaltrends.com/gaming/video-games-the-state-of-play-in-2010/
 
StatCrunch. (2019). Video game survey data project report. Retrieved from https://www.statcrunch.com/5.0/viewreport.php?reportid=88009">Video Game Survey Data Project Report
 
Triola, M. F. (2015). Essentials of statistics (5th ed.). Upper Saddle River, NJ: Pearson.

HTML link:
<A href="https://www.statcrunch.com/5.0/viewreport.php?reportid=88009">Video Game Survey Data Project Report</A>

Comments
Want to comment? Subscribe
Already a member? Sign in.

Always Learning