PLEASE CREATE AN R SCRIPT BASED OFF OF THIS QUESTION : summary$-$ The gender inequality index $($GII$)$provides insights into gender disparities in health, empowerment and the labor market. The GII is a composite measure, reflecting inequality in achievements between women and men in three dimensions: reproductive health, empowerment and the labor market.

The health dimension is measured by the maternal mortality ratio and the adolescent fertility rate.

The empowerment dimension is measured by the share of parliamentary seats held by each gender, and by secondary and higher education attainment levels.

The labor dimension is measured by women's participation in the workforce.

The GII varies between $0$and with higher values representing more equal outcomes. It is designed to reveal the extent to which national human development achievements are eroded by gender inequality, and to provide empirical foundations for policy analysis and advocacy efforts.

Instructions:

$$Create a histogram and a smoothed density estimate of the $2006,2010,$and $2013$scores$.$

Next create a box and whisker plot of the same data.

Calculate summary data for each year you have plotted. Have the means changed over time? How about the standard deviations?

Do the data look normally distributed based on what you know thus far?

Calculate the z$-$scores for each of the years $(2006,2010,2013).$

Create a confidence interval for the mean for each of the years $(2006,2010,2013).$

Re$-$Import the data and remove the rows with missing data using na$.$omit if you haven't already.

What test would you use to compare the global average GII for $2006$to the global average GII for $2013$and why?

Set up this test in words and mathematically

Run this test. What are your results? Do your confidence intervals for these two years overlap?

THE DATA TABLE IS IN THE IMAGE$($This is all the information I can provide$)$