Section 9.2
a) Let x represent the number of loads of laundry each sister use per week
Let y represent liters of water Sharon uses to wash her car each time
Sharon
225x
y
225x+y
Laundry
Car wash
Total
Interpolation and Extrapolation
Had the Games been held in 1940 and 1944, estimate what the winning heights would have been
and justify your answers.
Year 1940 = Year # 2
Verify:
Year 1944 = Year # 3
After adjustments, the Base-10 Logarithm function on this new set of axis is:
Formula:
Variables:
y: Heights(cm)
x: Years
: Vertical stretch by a factor of
: Horizontal stretch by a factor of
: Horizo
Another function that models that data: Sinusoidal Function
Formula:
Variables:
y: Heights(cm)
x: Years
: amplitude of this function is 19.21
period of this function is
: phase shift of to the left
:
If we apply the previously calculated Base-10 Logarithm function,
to this new set of combined data, we will see that it no longer fits because the x-values of that
function has been shifted.
RMSE=26.7
Use your model you predict the winning height in 1984 and in 2016. Comment on your answers.
Year 1984 = Year # 13
Although the predicted height in year 1984 is a little lower than the height achieved
Base-10 Logarithm Fit:
Zoomed-out graph:
Formula:
Variables:
y: Heights(cm)
: Vertical stretch by a factor of 3398
x: Years
: Horizontal stretch by a factor of
Above parameters are all with respect to
Linear Fit:
Formula:
Variables:
y: Heights(cm)
x: Years
Slope:
y-intercept:
RMSE: 4.523cm
Root Mean Square Error (RMSE) is when you take the square root of the sum of all differences
between the estim
Data Analysis
The table below gives the height (in centimeters) achieved by the gold medalists at various
Olympic Games.
Year
Height(cm
)
1932
197
1936
203
1948
198
1952
204
1956
212
1960
216
1964
218
After comparing the above three graphs, Linear Fit, Sine Fit, and Base-10 Logarithm Fit, we can
see that the RMSE value of the Sine Fit is the lowest. Theoretically, this would be the best
function to