Data set 1. Body Temperature
[Info]
Owner: bao16c
Source:
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Description: Data taken from the Journal of Statistics Education online data archive. That archive in turn got the data from an article in the Journal of the American Medical Association. (Mackowiak, et al., "A Critical Appraisal of 98.6 Degrees F …", vol. 268, pp. 157880, 1992).
"Body Temp" is measured in degrees fahrenheit
"Heart rate" is the resting beats per minute
Size: 2KB
Delimiter: space
Last edited: Oct 11, 2017
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Result 1: Scatter Plot [Info]
Owner: bao16c
Size: 174B
Created: Nov 6, 2017
The two quantitive data values I used were body temperature and heart rate. The scatter plot is positive, however the data is spread out quite a bit.
Yes, their are outliers that should be removed such as (100,78), (98,89), (98.2,57), (98.7,59), (99.3,63), (97.1,82), (97,80), (96.8,75),(97.7,84)
An appropriate significance level for my data would be .05 which will allow for a greater margin of error.
Result 2: Simple Linear Regression [Info]
Owner: bao16c
Size: 3KB
Created: Nov 9, 2017
Simple linear regression results:
Dependent Variable: Heart Rate Independent Variable: Body Temp Heart Rate = 166.28472 + 2.443238 Body Temp Sample size: 130 R (correlation coefficient) = 0.2536564 Rsq = 0.064341571 Estimate of error standard deviation: 6.8577393
Parameter estimates:
Parameter  Estimate  Std. Err.  Alternative  DF  TStat  Pvalue 

Intercept  166.28472  80.912346  ≠ 0  128  2.0551217  0.0419  Slope  2.443238  0.82351902  ≠ 0  128  2.9668265  0.0036 
Analysis of variance table for regression model:
Source  DF  SS  MS  Fstat  Pvalue 

Model  1  413.94842  413.94842  8.8020594  0.0036  Error  128  6019.6593  47.028588    Total  129  6433.6077    

My correlation coefficient is .25 which representing a fairly weak correlation between body temperature and heart rate.
My terms are significant because my pvalue is .0036 which is way below .05.
The line of best fit would be 166.3 heart rate and the slope would be a rise of 2.44. Therefore for every increase in heart rate theres a 2.44 increase in heart rate.
R squared is approximately .06 which represents that 6% of the variation in body temperature is accounted for heart rate.
Result 3: Scatter Plot line [Info]
Owner: bao16c
Size: 174B
Created: Nov 11, 2017
The line of best fit is not a good fit for my data because it only hits about 7 data points throughout the graph. There are data points not being represented by the line of best fit.
There is a very weak correlation between the heart rate and body temperature. There is no causation between the two variables.
<A href="https://www.statcrunch.com/5.0/viewreport.php?reportid=73382">Body Temperature Part 2</A>
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Nov 14, 2017
Nice report !