For numbers 1 to 3: The thermal condition in a cave is critical for sustaining a bat population. A sudden change in the temperature is related to deaths of bats in hundreds. An attempt to measure the degree of association between the temperature (in °C) and death toll (number of deaths) was done using 20 caves with reported cases of massive death among bats. Assume that temperature and death

MATLAB: An Introduction with Applications
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For numbers 1 to 3: The thermal condition in a cave is critical for sustaining a bat population. A sudden change in the temperature is
related to deaths of bats in hundreds. An attempt to measure the degree of association between the temperature (in °C) and death toll
(number of deaths) was done using 20 caves with reported cases of massive death among bats. Assume that temperature and death
toll are bivariate normal. Given below is the R software output:
> cor.test(temp, death)
Pearson's product-moment correlation
data: temp and death
t -1.4403, df- 148, p-value - 0.1519
alternative hypothesis: true correlation is not equal to e
95 percent confidence interval:
-0.27269325 0.04351158
sample estimates:
cor
-o1175698
1. The use of the parametric correlation analysis for the above study is valid because
O A. the independent and dependent variables are identified
O B. the variables are measured in ordinal level
O C. the collected data are quantitative in nature
O D. one variable will predict the other variable
Transcribed Image Text:For numbers 1 to 3: The thermal condition in a cave is critical for sustaining a bat population. A sudden change in the temperature is related to deaths of bats in hundreds. An attempt to measure the degree of association between the temperature (in °C) and death toll (number of deaths) was done using 20 caves with reported cases of massive death among bats. Assume that temperature and death toll are bivariate normal. Given below is the R software output: > cor.test(temp, death) Pearson's product-moment correlation data: temp and death t -1.4403, df- 148, p-value - 0.1519 alternative hypothesis: true correlation is not equal to e 95 percent confidence interval: -0.27269325 0.04351158 sample estimates: cor -o1175698 1. The use of the parametric correlation analysis for the above study is valid because O A. the independent and dependent variables are identified O B. the variables are measured in ordinal level O C. the collected data are quantitative in nature O D. one variable will predict the other variable
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