Hypothesis

* High fertility rates and high unemployment rates affect and increase Infant mortality rate of a country.

What is Infant Mortality Rate?

The infant mortality rate is defined as the number of children who die before their first birthday divided by the total number of births that took place that year.

What is Fertility Rate?

* Fertility rate of country is defined as the average total number of children born to one woman * A fertility rate of two children per women is considered the replacement rate at which a country can be stable.

What is Unemployment Rate?

* Unemployment rate represents the percent of labour force that is currently out of work.

* In other words, this figure represents the percentage of people who are of age to work and are capable of doing so but cannot find work.

Steps to Finding a Sample

* Use stratified random sample

* Dividing the world into continents

* Choose countries from continents based on the proportion of their population with relation to the world

* Calculating the percentage into 70 (which was the desired sample size) fairly enough. Sample

* Asia 45,

* Africa 10,

* Europe 8,

* North and South America 10,

* Australia/ Oceania 1

Bias

* While doing my project I encountered a lot of bias, most of it was sampling bias because I couldn’t find data from the entire population of some countries, so I had to do a lot of more research for those countries and look out at different sources to make sure the data was accurate. * The websites where I took my data from could have encountered bias such as non-response bias and response bias.

Single variable analysis: Infant mortality rate

* This bar graph represents Infant Mortality Rate around the world, it can be seen that there is a inconsistent trend in infant mortality rates globally. * Based on mean the average rate of infant mortality is approximately 28, which is a moderate number for the entire world considering the vast differences in rates around the world. * The mode being 21, demonstrates that this rate is the most common in countries around the world.

Histogram

While in the bar graph standard deviation demonstrated an unsteady pattern, the histogram shows that there are fewer countries with a Skewed Right pattern as infant mortality rate increases. This shows that fewer countries have a high infant mortality rate.

Unemployment rates

* The mean for this data is roughly 12 which means that on average 12% of the world’s work force in unemployed.

* Inconsistent trend

* The mode is 4 which means that the most common percentage of unemployed work force among the countries included was 4%.

Fertility rates

* This data has a mean of approximately 3 which represents the average number of children women bear worldwide. * A mode of 2.5 in this graph shows that globally, the most common number of children per women is between 2 and 3 which by demographic standards is the stable fertility rate in order for a population to be at stable level. * The median of 2 as well represents that globally the fertility rate is at an appropriate level. The mean, median and mode are all very similar; this represents a much more consistent pattern globally in terms of fertility rate as opposed to infant mortality rate. * Standard deviation is approximately 2 also which proves the consistency of the trend internationally.

Fertility rate DOUBLE VARIABLE

* The graph shows a strong positive correlation between these two variables. (infant mortality and fertility rate) * The coefficient of determination translates to 68.8 % of the variance in the infant is influenced by variance in the fertility rate. * the correlation is strong.

* This graph reflects that the more the amount of births increases in a country the higher the infant mortality will be. In other words, as fertility increases there will be more babies to die.

Unemployment Rate: DOUBLE VARIABLE

* The following scatter plot shows the relationship between infant mortality rate and unemployment rate. * The correlation can be describe as a weak positive correlation because the R^2 value is 0.215 much closer to 0 than it is to 1; therefore there is a 21.5% variation of the infant mortality rate. * An insignificant average increase in infant mortality rate is produced by the unemployment rate increase. This shows that unemployment rates don’t have as much as an impact as fertility rate on infant mortality.

CONCLUSION

In conclusion, based on the data collected and analyzed the report disproved my hypothesis because I stated that both of the variables will increase dramatically the infant mortality rate of a country. part of my conclusion was accurate regarding the fertility rate impacts on infant mortality rate, however unemployment rates seem to not have as much as an impact on infant mortality rate. Although there was a slight correlation between unemployment rates and infant mortality rates I thought the correlation was going to be stronger than what I actually got. A possible explanation to this relationship can be that a family may not be able to obtain money through a job but they still see their children’s well-being as a priority and they manage to take care of them. If I had to do this project again I’ll get data from different years and from many countries as possible I guess.