# phone contacts vs gpa

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Phone Contacts Vs GPA. Is there a Correlation between the number of Contacts in someone's phone and their G.P.A?. Intro. We felt that the number of phone contacts vs. GPA was a unique comparison We felt that any correlation would be interesting to see; even if there was no correlation. - PowerPoint PPT Presentation

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• Phone Contacts Vs GPAIs there a Correlation between the number of Contacts in someone's phone and their G.P.A?

• IntroWe felt that the number of phone contacts vs. GPA was a unique comparisonWe felt that any correlation would be interesting to see; even if there was no correlation

• Univariate Analysis of GPAMean X= 3.45 SX= .476

Outlier test=Q3-Q1 * 1.5= .7125 Outlier=2.74

• Univariate Analysis of ContactsMean X= 93.576 SX= 60.597

Outlier test=Q3-Q1 * 1.5= 158.25 Outlier=-64.674

• Explanatory & Response VariableExplanatory = GPAResponse= # of Phone Contacts

The GPA of a student affects the amount of contacts they have in their phone because people with higher GPAs spend more time studying, and therefore less time with friends

• DataForm: LinearDirection: NegativeStrength: Moderate

Chart1

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Sheet1

3.9555

3.760

3.7102

3.730

4.0460

3205

3.3330

3.64111

3.5104

3.7155

3.7114

3.670

3.590

3.25140

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3.67187

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3.52116

3.8431

3.737

3.532

3.5177

3.744

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2.5228

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3100

3.941

2.7140

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3.4160

1.8190

Sheet1

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• GPA Contacts GPA ContactsRaw Data

3.95553.7603.71023.7304.046032053.33303.641113.51043.71553.71143.6703.5903.251403.2283.6718741003.52116

3.84313.7373.5323.51773.7443.5833272.522832031003.9412.71404213.41601.8190

• VariationExplained variation = sum ( y-mean)2= 25453.37673Unexplained variation = sum (y )2=92048.68388Total variation = sum (y y-mean)2=117502.0606

• r = -.4654, r2= .2166 or 21.7% c.v=.335 so r>c.v Regression line Y= 297.9936 + -59.309x There is a Negative correlation between the GPA and number of contacts. The lower the GPA= More contacts; Higher GPA= Less contacts.

• X

Y

GPA # of contacts

• Histogram contdBoth histograms have an equal distribution For GPA: Outliers are 1.8, 2.5, 2.7 For Contacts: No OutliersConforms with Empirical Rule Test

• Empirical Rule TestEmpirical Rule Test for GPA:68% of the data falls between the values 3.591 0.3445 = 3.24653.591 + 0.3445 = 3.935595% of the data falls between the values3.591 2(0.3445) = 2.9023.591 + 2(3.445) = 4.2899.7% of the data falls between the values3.591 3(0.3445) = 2.55753.591 + 3(0.3445) = 4.6245Empirical Rule Test for Current Events Scores:68% of the data falls between the values0.6445 0.2896 = 0.35490.6445 + 0.2896 = 0.934195% of the data falls between the values0.6445 2(0.2896) = 0.06530.6445 + 2(0.2896) = 1.223799.7% of the data falls between the values0.6445 3(0.2896) = -0.22430.6445 + 3(0.2896) = 1.5133

• Standard Errorse =se =se =54.49

• E = 68.19 95% Prediction Interval (X0 = 3.7)

• 95% Prediction Interval (contd)10.361 < y < 146.741There is a very large prediction interval, due in part to the small r and r2 values.

• ResidualsThis shows linear correlation because the plots are randomly scattered and there is no patter on the residual graph

• Conclusion

In conclusion we found out that there was a weak correlation on students GPA and the amount of contacts they have in their phone. Since it was so weak it is only true a very little % of the time.4.9 GPA- 4 contacts (Mom, Dad, Home, and Steve)

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