# 3 slides powerpoint presentation

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Signature assignment powerpoint presentation. I am attaching an excel file that you will use. Please be precise

Health Services and Nursing Scenar
Scenario 1
Year
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
Predicting the Number of Babies Born
Review the data involving the number of babies born in Humboldt County from 2006-2015. Predict the n
Babies Born in
Hombolt County
275
280
320
366
358
336
375
390
455
487
Scatter Plot with Linear
Babies Born in Hombolt County
600
Babies born in Hombolt
Topic 1
500
400
300
200
100
0
2005
2006
2007
2008
2009
2010
Linear Regreession Equation
y=21.139-42137
R-square
0,879
Better Fit
The exponential model is a better fit as the coefficient of determination(R
is greater for exponential model(R-square=0.8935) compared to linear reg
For exponential model,89.35% of the variation in the babies born in Homb
whereas for linear regression 87.9% of the variation in babies born in Hom
Thus,exponential model is a better fit.
Predicting the number of babies born in 2018(Usin
Exponential Mode
y=10^(-48)*e^(0.0578x)
Here,x=2018
y
Number of Babies
453,19
454 (Round to the nearest integer)
d Nursing Scenario
y from 2006-2015. Predict the number of babies who will be born in 2018.
Using Insert–>Chart–>Scatter in Excel
Scatter Plot with Linear Trend Line
Scatter Plot with Expone
y = 21,139x – 42137
R² = 0,879
n Hombolt County
Babies Born in Hombolt County
Babies Born in Hombolt
600
2010
2011
2012
2013
2014
2015
2016
500
400
300
200
100
0
2005
2006
2007
2008
2009
Year
Exponential Equation Model
y=10^(-48)*e^(0.0578x)
R-square
e coefficient of determination(R-square)
=0.8935) compared to linear regression model(R-square=0.879).
ation in the babies born in Hombolt is explained by years,
e variation in babies born in Hombolt is explained by years.
bies born in 2018(Using Exponential Model, as it is the best fit)
0,8935
Scatter Plot with Exponential Trend Line
y = 1E-48e0,0578x
R² = 0,8935
ies Born in Hombolt County
2009
ation Model
2010
2011
Year
2012
2013
2014
2015
2016

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