question_for_statistics. x
analyze the data using pie charts,histogram,box and whisker,bar graphs,scattered plots and comment. find the mean,median and standard deviation and comment. find the correlation analysis of the data and comment. use any statistical package for this.
Running Head: Data analysis drawn from World Bank. 3
Year\Indicator Name 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 |
Life expectancy at birth, total (years) 77.82926829 78.07804878 78.4804878 78.63170732 78.93170732 79.23414634 79.63414634 79.93658534 80.23902439 80.4902439 80.84146341 81.04146341 81.29268293 81.39512195 |
CO2 emissions (metric tons per capita) 17.0116172 17.98153733 18.01715505 18.54058404 17.19979166 17.20903399 16.73412301 17.372691 17.4149047 17.35063038 18.01405569 18.2328628 18.07162335 18.56961909 |
Health expenditure per capita (current US$) 1574.279016 1767.721588 1766.049449 1597.620745 1754.984609 1728.461993 1644.80348 1858.490441 2339.219055 2888.976962 3157.754309 3330.212891 3956.468724 4229.033066 |
GDP growth (annual %) 3.939983314 4.181423944 3.972448021 4.585530281 5.15985438 3.951352155 2.071616393 3.903791221 3.272264035 4.155794748 2.959140943 3.081394099 3.564177973 3.832065489 |
Mobile cellular subscriptions (per 100 people) 12.37415015 21.77990754 24.71234651 26.25050454 33.32824218 44.67670207 57.43417616 64.62949928 72.31307069 81.97446237 90.27854017 95.25510508 100.662936 102.8176451 |
1 .Create appropriate plots (histogram, pie-charts, bar charts box and whiskers, scatter plots) and comment on the general trends present.
2. Calculate the mean, median, standard deviation for each variable and comment.
3. Perform correlation analysis of each variable with life expectancy. Comment on the result and the implied relationship .i. e .just because the two variables are highly correlated does this imply a cause and effect relationship? Discuss.