By Lauren Whitsell Scatter Plot This scatter plot shows data for the US Annual Wages The equation generates this line which was an r value of 96 That means the line is extremely close to the data which means the data rises in a linear fashion ID: 601836
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Slide1
Regression Project
By Lauren WhitsellSlide2
Scatter Plot
This scatter plot shows data for the US Annual Wages.
The equation generates this line, which was an
r
value of .96. That means the line is extremely close to the data, which means the data rises in a linear fashion.Slide3
Equation
A negative
y
-intercept means that the slope used to be more shallow, indicating that the rise of wages is greater than it has been in past years, because people cannot earn negative wages. The wages must have been a shallower line, growing slowly steeper in
earlier years,
and increasing faster approaching the modern era.Slide4
Predictions
Using the equation: , I predicted these points on the
scatterplot
:
X
Y
1988.5
37335.65
1989.5
37748.65
1991.5
38574.75Slide5
Conclusion
The data rises in a linear fashion based on the equation.
The r-value reveals a predictable data set.
The slope reveals data that slopped differently at a different point in time.
The scatter plot reveals data without irregularities. Therefore, wages in the US rise predictably. Economists and government officials can use this data to predict the how people will spend money.