Life Expectancies Is there a relationship between the life expectancy for men and the life expectancy for women in a given country? A random sample of nonindustrialized countries was selected, and the life expectancy in years is listed for both men and women. Are the variables linearly related? Men 56.8 53.6 70.6 61.5 44.6 51.7 Women 64.4 46.2 72.2 70.2 48.4 47.1 (a) Compute the value of the correlation coefficient. Round your answer to at least three decimal places. r= (b) Stat the hypotheses. H0: H1: (c) Test the significance of the correlation coefficient at a=0.01 and 0.10 using The Critical Values for the PPMC Table. Critical value(s): ± Reject/do not reject the null hypothesis (d) Give a brief explanation of the type of relationship. There is/is not (Choose one) a significant
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
Life Expectancies Is there a relationship between the life expectancy for men and the life expectancy for women in a given country? A random sample of nonindustrialized countries was selected, and the life expectancy in years is listed for both men and women. Are the variables linearly related?
| Men
|
56.8
|
53.6
|
70.6
|
61.5
|
44.6
|
51.7
|
|---|---|---|---|---|---|---|
| Women
|
64.4
|
46.2
|
72.2
|
70.2
|
48.4
|
47.1
|
|
(a) Compute the value of the
r= |
(b) Stat the hypotheses.
H0:
H1:
(c) Test the significance of the correlation coefficient at a=0.01 and 0.10 using The Critical Values for the PPMC Table.
Critical value(s): ±
Reject/do not reject the null hypothesis
(d) Give a brief explanation of the type of relationship.
|
There is/is not (Choose one) a significant |
|
(a) Compute the value of the correlation coefficient. Round your answer to at least three decimal places. r= |
(b) Stat the hypotheses.
H0:
H1:
(c) Test the significance of the correlation coefficient at a=0.01 and 0.10 using The Critical Values for the PPMC Table.
Critical value(s): ±
Reject/do not reject the null hypothesis
(d) Give a brief explanation of the type of relationship.
|
There is/is not (Choose one) a significant |
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