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# Fertility Analysis Assignment PDF

Added on - 23 Sep 2021

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Fertility1
REPORT ON FERTILITY ANALYSIS
NAME OF AUTHOR
NAME OF CLASS
NAME OF PROFESSOR
NAME OF SCHOOL
NAME OF CITY AND STATE WHERE IT IS LOCATED
THE DATE
Fertility2
Introduction
I am going to do the discussionof results to address the overall conclusion
of the empirical analysis and to show how valid internally and externally the
results are using correlation. We have been given a dataset that is dirty. By dirty I
mean that we have some empty cells in the data. We will import our data into Stata
and to view summary of the dataset, we write the code codebook. It will display all
the columns and their values. From there we can check the missing values and
compare them with the range. We also check if there are strange numeric values.
You can sort every columns using sort command to check strange values. We will
use the command ‘dropmiss’ to delete all rows with empty values. Cleaning data is
very important because it reduces circumstance of obtaining abnormal solutions. It
also makes the process of analyzing data simple. After cleaning our data, we will
go straight to obtaining the correlation of the dataset.
Correlation is a mutual relationship or connection between two or more
things or a quantity measuring the extent of the interdependence of variable
quantities. Analyzing the data that we have above in a regression, we will be
required to either show how education affects fertility, how age affects fertility,
how a marriage affects fertility, how living in the city affects fertility, how
electricity affects fertility and how owning television too affects fertility.
Fertility3
On the correlation part on how education affects fertility, we eventually have
to partition the education-fertility data separately. From the data given we have that
fertility is the number of living children and that is what we work with as our
fertility. After cleaning our data, we now check for the correlation using Stata. To
obtain correlation, we need to conduct a regression analysis using fertility as the
dependent variable. We will conduct two regression analysis both using fertility as
the dependent variable. During regression analysis, we will obtain values like R-
squared and Multiple R. R- squared is the line of best fit. It shows you how
accurate your procedure is. Multiple R is the square root of R- squared and its
value shows the correlation of the variables being determined during regression.
The correlation analysis of the relationship between the fertility and level of
a woman’s education which is the second of all our correlation analysis gives two
tables, and these are Regression statistics table consisting of multiple regression,
regression square, adjusted regression square, standard error, and observations. The
second table of interest which is the intercept-coefficient table consists of
coefficients, standard error, t Stat and P-value on the column parts. Our major
concern is on multiple regression and the coefficients which are different in value.
From the analysis of the Clean Fertility data, the second multiple linear regression
gives me a value of 0.321049969. This definitely by the rules of regression we
conclude that there is a weak relationship between education and fertility. By this,

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