You wish to determine if there linear correlation between the age of a driver and the number of driver deaths. The following table represents the age of a driver and the number of driver deaths per 100,000. Use a significance level of 0.01 and round all values to 4 decimal places. Driver Age Number of Driver Deaths per 100,000 58 29 24 30 65 21 43 22 28 20 78 27 60 21 56 25 Ho: ρ = 0 Ha: ρ ≠ 0 Find the Linear Correlation Coefficient r = Find the p-value p-value = The p-value is Greater than αα Less than (or equal to) αα The p-value leads to a decision to Do Not Reject Ho Accept Ho Reject Ho The conclusion is There is no Significant Correlation There is Significant Linear Correlation between driver age and number of driver deaths. There is Significant Positive Linear Correlation between driver age and number of driver deaths. There is Significant Negative Linear Correlation between driver age and number of driver deaths. There is no Significant Linear Correlation between driver age and number of driver deaths. The final conclusion is It appears that there is no linear relationship between driver age and the number of driver deaths. It appears that as driver age increases the number of driver deaths increase. It appears that as driver age increases the number of driver deaths decrease. As a person gets older, more driver deaths will occur.
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.
You wish to determine if there
| Driver Age | Number of Driver Deaths per 100,000 |
|---|---|
| 58 | 29 |
| 24 | 30 |
| 65 | 21 |
| 43 | 22 |
| 28 | 20 |
| 78 | 27 |
| 60 | 21 |
| 56 | 25 |
Ho: ρ = 0
Ha: ρ ≠ 0
Find the Linear
r =
Find the p-value
p-value =
The p-value is
- Greater than αα
- Less than (or equal to) αα
The p-value leads to a decision to
- Do Not Reject Ho
- Accept Ho
- Reject Ho
The conclusion is
- There is no Significant Correlation
- There is Significant Linear Correlation between driver age and number of driver deaths.
- There is Significant
Positive Linear Correlation between driver age and number of driver deaths. - There is Significant
Negative Linear Correlation between driver age and number of driver deaths. - There is no Significant Linear Correlation between driver age and number of driver deaths.
The final conclusion is
- It appears that there is no linear relationship between driver age and the number of driver deaths.
- It appears that as driver age increases the number of driver deaths increase.
- It appears that as driver age increases the number of driver deaths decrease.
- As a person gets older, more driver deaths will occur.
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