What John's Salary Will Be If William If He Has 5 Years Of Education
Abstract
In this paper there is a given set of data from 4.2 - Assignment: Correlation and Regression that will be used to answer questions a,b, and c. The data is from working technicians in maintenance at the Atlanta International Airport and displays the amount of education (in years) to the mechanics income. It will also be determined if there is a positive or negative linear correlation for each variable (x and y). For question a, the relationship and results will be discussed for the number in years of education to the salaries earned in statistical terms. Question b will determine the expected yearly salary of William if he has 16 years of education. Question c will determine what John’s salary will be if he has 5 years of education. …show more content…
Generated using StatCrunch software.
Figure 2. Scatter plot with regression line (fitted line plot).
Correlation between education and salary is: y(x*y) = square root of 0.85250754 = 0.92331335
There is a positive linear relationship between x and y variables because both x and y increase. If x and y had a negatively linearly correlation then y would decrease and x would increase (Weiss, 2016).
B. Using the data and results provided in question a will be used to calculate the answer. If William has 16 years experience then he will earn a yearly salary of $42,790. To calculate the answer, find y if x = 16. y=3.36x - 10.97 y=3.36(16) - 10.97 y= 53.76 - 10.97 y= 42.79
Therefore, Williams expected yearly salary would be $42,790.
c. Using the data calculated in question a, John’s education of 5 years will give him an expected salary of $5830. To calculate the answer, find y if x = 5. y= 3.36(x) - 10.97 y= 3.36(5) - 10.97 y= 16.8 - 10.97 y= 5.83
Therefore, John will earn and expected yearly salary of
In this paper there is a given set of data from 4.2 - Assignment: Correlation and Regression that will be used to answer questions a,b, and c. The data is from working technicians in maintenance at the Atlanta International Airport and displays the amount of education (in years) to the mechanics income. It will also be determined if there is a positive or negative linear correlation for each variable (x and y). For question a, the relationship and results will be discussed for the number in years of education to the salaries earned in statistical terms. Question b will determine the expected yearly salary of William if he has 16 years of education. Question c will determine what John’s salary will be if he has 5 years of education. …show more content…
Generated using StatCrunch software.
Figure 2. Scatter plot with regression line (fitted line plot).
Correlation between education and salary is: y(x*y) = square root of 0.85250754 = 0.92331335
There is a positive linear relationship between x and y variables because both x and y increase. If x and y had a negatively linearly correlation then y would decrease and x would increase (Weiss, 2016).
B. Using the data and results provided in question a will be used to calculate the answer. If William has 16 years experience then he will earn a yearly salary of $42,790. To calculate the answer, find y if x = 16. y=3.36x - 10.97 y=3.36(16) - 10.97 y= 53.76 - 10.97 y= 42.79
Therefore, Williams expected yearly salary would be $42,790.
c. Using the data calculated in question a, John’s education of 5 years will give him an expected salary of $5830. To calculate the answer, find y if x = 5. y= 3.36(x) - 10.97 y= 3.36(5) - 10.97 y= 16.8 - 10.97 y= 5.83
Therefore, John will earn and expected yearly salary of