Lets make this a little easier. It doesn't matter where values come from, there will be always variation in a set of collected numbers. The more complex the system, the greater the likelihood of significant variations. In this case, we don't have any significant variations. How is that possible? This is actually how a vast majority of in-house fraud is caught in production processes. People know what the outcome data "should" look like, but don't know enough about the input processes to really make believable fake underlying data.
The numbers are obviously manipulated because they are "too perfect". Lets start with aggregate data and then go from there. Instead of having some days that there are huge spikes and other days with little loss of life (ie a major battle one day and then the IDF pulling back to regroup the next or bombing a market one day and not the next), the daily loss of life was 270+- 15% or a range of 230 - 311 . Where are the peaks and valleys in the data? Any form of casualty data of civilian populations will have a significantly greater spread than what is being portrayed. As an example, the war(s) in the Balkans showed massive variation in civilian losses on a daily (and even weekly) basis. Where are the outliers here? We should be seeing days of 400-500 and days of 50-100, not an almost perfect set of data confined to a set of boundary criteria with a mean of 270.
Then you fall into the issue that the number of children casualties is not tied to the number of women casualties. How is that possible in this type of indiscriminate bombing? Then the number of women killed is strongly negatively related to the number of male casualties. So when men die in combat that day, then the daily reporting of female losses goes down predictably. But yet the loss of the children remains unrelated to the men. In what scenario is that logically possible? Then you get to the weird data artifacts like when the few days that male losses were at or close to 0, the female death toll for the day skyrockets (while the children casualty figures remained steady those days). How does that play out in a combat scenario?
This data was being generated not reported, with a specific daily number in mind. More than likely they decided that the daily losses should be approximately 70% women and children and 30% males. So they did some type of random assignment and went from there. Once they had a women and children number, they then subtracted that off from the random number selected from the 230-311 "expected" casualty figure and then took out the women and children to get the males. Those steps would mirror the weird artifacts in the data.
So what are the real numbers? Who knows. All I can tell you is that these values are obviously manipulated.