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Jeff Pratt Math 1040 4-11-12 Term Project written reportThe purpose of our study was to find out if there was any correlation between the age of a personand the number of personal handheld electronic devices that the person owns.Each member of our group was to interview a minimum of 5 people per day for 5 different days.We would simply as the age of the person and how many personal electronic devices theyowned. (Phones, laptops, gaming devices, ect.). We also determined that going to a public placesuch as a grocery store or library would help eliminate any sample bias. For example,interviewing on SLCC campus might give you results of a younger crowd. Also, on a campusyou might find people with more devices that students use for their studies. All data would thenbe jointed to see if there was a correlation.All data organized in a Contingency tableRows: AGEColumns: Number of electronic devices 0 1 2 3 4 5 6 9 11 12 Total2 0 0 1 0 0 0 0 0 0 0 15 0 0 1 0 0 0 0 0 0 0 114 0 0 0 0 1 0 0 0 0 0 116 0 0 0 0 1 0 0 0 0 0 117 0 2 0 0 0 0 0 0 0 0 218 0 1 1 0 1 1 0 0 0 0 419 0 0 0 2 0 1 0 0 0 0 320 0 0 0 1 0 0 0 0 0 0 121 0 0 1 1 1 0 0 0 0 0 322 0 0 1 2 0 0 0 0 0 0 323 0 1 2 1 1 1 0 0 0 0 624 0 0 0 2 0 0 1 1 0 0 425 0 0 1 3 0 1 0 0 0 0 526 0 1 1 3 2 1 1 0 1 1 1127 0 1 0 4 2 1 0 0 0 0 8
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Summary statistics for second variable (# OF DEVICES): Column Mode Mean Variance Std. Dev. Std. Err. Median Range Min Max Q1 Q3Electronic devices 3 2.9274194 4.03534 2.0088155 0.18039696 3 12 0 12 2 4 IQR = 2 Upper fence= 4+1.5(2) = 7 Outliers = 9, 11, 12, 12
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Linear correlation coefficient = -0.2409Equation for line of regression Y = 3.9497154 – 0.028213825X
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Difficulties and surprises: While collecting my data I came across a few difficulties. The main challengewas I had to select people at random while still trying to get a diverse age range. At the grocery storeyou are more likely to see middle aged people and not so many teenagers.Another difficulty was I had to explain what kinds of different devices constitute a personal handheldelectronic device. I was also worried that I might be inconveniencing some people, being that mostpeople don’t have that kind of information right on the top of their head so it took some thought.Analysis: According to what I found from the data, it doesn’t seem that there exists much of acorrelation between age and personal electronic devices. Our correlation coefficient of -0.2409 is furtherevidence of that. The value -0.2409 only hints at a very small negative correlation, suggesting that as agegoes up, the number of personal handheld devices goes down. However, in order to be able to statewith confidence that there is in fact a correlation, the value of R must be closer to a +1 or -1.DF = 124 – 2 = 122With a level of significance of 0.05, the critical value for the sample size is roughly .195When comparing the critical value with the value of R, since the value of R is “greater” (further fromzero) than the critical value, this means that there is a statistically significant correlation. Although Iwould have thought it would have been a stronger correlation.Conclusion: Upon collecting the data I initially did not see much of a correlation. However, when Icompared the value R to the critical value it showed that there is indeed a significant negativecorrelation between age and the number of personal handheld electronic devices. I believe that with allof our data we were able to answer our original research question.
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