The Russian Invasion of Ukraine has led to devastating effects on the Russian and global Economy (Liadze et al, 2022).Reports indicate that there is conflicting information on the state of war in Ukraine as regards the amounts of losses that Russia has incurred in form of military equipment in Russia since its invasion in Ukraine on February 24th 2022 (Mittal, 2022).
Mittal (2022) argues that the Russia Military has lost more war equipment than the Ukrainian forces. The purpose of this study is to establish what effect the Russia-Ukraine war has had on the Russian Military paraphernalia. This study will use data from https://www.kaggle.com/datasets/piterfm/2022-ukraine-russian-war titled 2022 Ukraine Russia War.

According to the Atlantic Council military fellows (2022), the Russian invasion into Ukraine turned from an attempt to take over the Ukrainian capital Kyiv to a full-fledged war targeted at demilitarizing Ukraine.However, as it turned out, the Ukrainian defense forces put up a strong defense, destroying dozens of Russian crafts and tanks thus stalling the Russian operations greatlyAtlantic Council military fellows (2022) report that Russian forces have suffered major equipment loss as a result of the warThe 2022 Russia Ukraine war data presented in the following section will shed light on incurred losses

A total of 64 observations from February 25th, a day after the war started to 29th April 2022 was used.The output below shows the army equipment in the dataset whose losses were estimated from the data

##  [1] "ï..date"               "day"                   "aircraft"             
##  [4] "helicopter"            "tank"                  "APC"                  
##  [7] "field.artillery"       "MRL"                   "military.auto"        
## [10] "fuel.tank"             "drone"                 "naval.ship"           
## [13] "anti.aircraft.warfare" "special.equipment"     "mobile.SRBM.system"

A summary statistics output is shown below giving means, medians, max, min and quartiles

##    ï..date               day           aircraft       helicopter    
##  Length:64          Min.   : 2.00   Min.   : 10.0   Min.   :  7.00  
##  Class :character   1st Qu.:17.75   1st Qu.: 70.0   1st Qu.: 85.25  
##  Mode  :character   Median :33.50   Median :125.0   Median :128.00  
##                     Mean   :33.50   Mean   :114.1   Mean   :112.14  
##                     3rd Qu.:49.25   3rd Qu.:158.5   3rd Qu.:143.25  
##                     Max.   :65.00   Max.   :189.0   Max.   :155.00  
##                                                                     
##       tank            APC       field.artillery      MRL        
##  Min.   : 80.0   Min.   : 516   Min.   : 49.0   Min.   :  4.00  
##  1st Qu.:371.0   1st Qu.:1221   1st Qu.:138.8   1st Qu.: 62.00  
##  Median :591.5   Median :1702   Median :302.5   Median : 95.50  
##  Mean   :562.4   Mean   :1605   Mean   :263.3   Mean   : 89.91  
##  3rd Qu.:742.5   3rd Qu.:1965   3rd Qu.:360.0   3rd Qu.:116.75  
##  Max.   :986.0   Max.   :2418   Max.   :435.0   Max.   :151.00  
##                                                                 
##  military.auto      fuel.tank         drone          naval.ship   
##  Min.   : 100.0   Min.   :60.00   Min.   :  0.00   Min.   :2.000  
##  1st Qu.: 596.2   1st Qu.:60.00   1st Qu.:  7.00   1st Qu.:3.000  
##  Median :1164.0   Median :73.00   Median : 68.50   Median :7.000  
##  Mean   :1037.3   Mean   :69.22   Mean   : 77.28   Mean   :5.328  
##  3rd Qu.:1431.0   3rd Qu.:76.00   3rd Qu.:132.50   3rd Qu.:7.000  
##  Max.   :1695.0   Max.   :76.00   Max.   :229.00   Max.   :8.000  
##                                                                   
##  anti.aircraft.warfare special.equipment mobile.SRBM.system
##  Min.   : 0.00         Min.   :10.00     Min.   :2.000     
##  1st Qu.:33.75         1st Qu.:21.00     1st Qu.:4.000     
##  Median :54.00         Median :25.00     Median :4.000     
##  Mean   :46.14         Mean   :22.73     Mean   :3.943     
##  3rd Qu.:64.00         3rd Qu.:27.00     3rd Qu.:4.000     
##  Max.   :73.00         Max.   :31.00     Max.   :4.000     
##                        NA's   :19        NA's   :29

From the output, it can be observed that on average, Russia has lost tanks, APCs and military autos the most with relatively fewer naval ships, fuel tanks and drones lost

To understand how Russia is progressing over time in terms of losses made, a plot of aircrafts, tanks and naval ships lost versus progress in days of war is presented below;

## Warning in apply(russia_losses, 2, as.numeric): NAs introduced by coercion

### From the plots above, it can be observed that since the beginning of the war, the Russian forces record an increasing number of losses every passing day. The boxplot below shows the means, medians and quartiles for all the equipment. APC and military autos were the most destroyed in the war ### The histogram below shows the distribution of Russian aircrafts, APCs and Tanks lost ### From the above histograms, it can be observed that the dataset follows a poisson distribution which resembles a normal distribution for heavily lost equipment since the shape of the distributions is bell-like but for drones the distribution is skewed to the left.

INTERPRETATION OF VISUALIZATIONS The visualizations show that the Russian army is suffering immense losses in terms of the equipment lost in the war.From the scatterplot, it can be observed that in all cases where a scatterplot was run, there was a positive relationship between the count of losses and the days.The meaning of the positive relationship is that as the war progresses, the Russian forces will most likely incur even more military equipment losses. Furthermore, the data shows that Russia will most likely also lose a higher number of tanks and APCs compared to other equipment like drones and naval ships which have recorded lower, but increasing losses.The distributions also show that a majority of the dataset has a Poisson distribution, which implies that the linearity assumption for log counts can be made. The assumptions then tell us that the continued existence of war will lead to more military equipment losses for Russian forces

CONCLUSION AND RECOMMENDATION From the data visualizations, it can be established that the Russian invasion of Ukraine has led to massive losses on the Russian defense forces in terms of the military equipment lostThe data also shows that the Russian Forces are likely to lose more APCs and tanks in the future if the war persists as the trend for the losses show a steady increase of losses with time.This study would therefore be of the opinion that the Russian Ukraine conflict will have a damaging effect on the Russian war artillery inventory which may also have ripple effects for the Russian economy as it tries to recover.This study therefore recommends more compelling studies to be undertaken in an attempt to highlight what effects the Russian Ukraine conflict may have on both the Russian, Ukrainian and global economy.

REFERENCES Atlantic Council military fellows (2022, 3 16). Russia Crisis Military Assessment: The weapons Ukraine needs most to win the war. Retrieved from Atlantic Council: https://www.atlanticcouncil.org/blogs/new-atlanticist/russia-crisis-military-assessment-the-weapons-ukraine-needs-most-to-win-the-war/Iana Liadze, Corrado Macchiarelli, Paul Mortimer-Lee,Patricia Sanchez Juanino, C. M.-L. (2022). The Economic Costs of the RussiaUkraine Conflict. National Institute of Economic and Social Research.Mittal, V. (2022). Military Equipment Losses Provide Insight Into Russia-Ukraine War. Retrieved from Forbes: https://www.forbes.com/sites/vikrammittal/2022/03/10/military-equipment-losses-provide-insight-into-russia-ukraine-war/?sh=2615699f6f59

APPENDIX: R-CODE