What is the equation to predict mortality rates from obesity rates? O Mortality.rate = 13.458199 - 0.21749489 Obesity.rate Obesity.rate == 13.458199 0.21749489 Mortality.rate O Mortality.rate Mortality.rate 13.458199 - 0.0067 Obesity.rate = 13.458199 + 0.21749489 Obesity.rate
Contingency Table
A contingency table can be defined as the visual representation of the relationship between two or more categorical variables that can be evaluated and registered. It is a categorical version of the scatterplot, which is used to investigate the linear relationship between two variables. A contingency table is indeed a type of frequency distribution table that displays two variables at the same time.
Binomial Distribution
Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.
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Homework 2.2-2.4
25. Colorectal cancer (CRC) is the third most commonly diagnosed cancer among Americans (with nearly 147,000 new cases), and the third leading cause of cancer death (with over 50,000 deaths annually). Research was
done to determine whether there is a link between obesity and CRC mortality rates among African Americans in the United States by county. Below are the results of a least-squares regression analysis from the
software StatCrunch.
Simple linear regression results:
Dependent Variable: Mortality.rate
Independent Variable: Obesity.rate
Mortality.rate = 13.458199 - 0.21749489 Obesity.rate
Sample size: 3098
R (correlation coefficient) = -0.0067
R-sq = 4.5304943E-5
Estimate of error standard deviation: 111.20661
Parameter estimates:
Parameter Estimate
Std. Err. Alternative DF
T-Stat
P-Value
Intercept
13.458199 15.9797735
+0 3096 0.84220207 0.3997
Slope
-0.21749489 0.5807189
#0 3096 -0.37452698
0.708
Analysis of variance table for regression model:
Source DF
MS
F-stat
P-value
Model
1
1734.7122 1734.7122 0.14027046
0.708
Error
3096 3.8287952E7 12366.91
Total
3097 3.8289688E7
What is the equation to predict mortality rates from obesity rates?
O Mortality.rate = 13.458199 - 0.21749489 Obesity.rate
O Obesity.rate = 13.458199 - 0.21749489 Mortality.rate
O Mortality.rate = 13.458199 + 0.21749489 Obesity.rate
O Mortality.rate = 13.458199 - 0.0067 Obesity.rate
26. Colorectal cancer (CRC) is the third most commonly diagnosed cancer among Americans (with nearly 147,000 new cases), and the third leading cause of cancer death (with over 50,000 deaths annually). Research was
done to determine whether there is a link between obesity and CRC mortality rates among African Americans in the United States by county. Below are the results of a least-squares regression analysis from the
software StatCrunch,
Simple linear regression results:
Dependent Variable: Mortality.rate
Indenendent Variahle: Obesitv rate
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the predict mortality rates from obesity rates
the normal regression equation is Y = a + b X
here Y is dependent variable
b is slope
a is intercept
X is independent variable
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