10.4.1 General Examples

In this Section, some general examples of data interpretation are given.

Small x-standard deviation, large y-standard deviation

this is a vertically strung group; If both x and y averages are small, the group is centered around the point of aim, and is most likely strung due to a velocity or deceleration effect (such as fairly large shot-to-shot velocity variations). Barrel vibrations and bullet stabilization effects cannot be ruled out based on a single range-to-target experiment.

Small standard deviation, large range

this data set may contain 'bad data,' but care must be exercised. There may be simply a bad shot (shooter error), but DSB Scientific has seen handloads that gave a 4 tight shot, one bad shot pattern very reproducibly.

This may indicate a very subtle barrel vibration or bullet stabilization effect. Perhaps you can check for such an effect by a slight change in powder charge, both larger and smaller, or a small change in bullet weight (keeping the manufacturer and type/style bullet the same), changing neck tension slightly, etc. Bullet run-out should be checked, since there may be high run-out loads only intermittently. Carefully assessing the cause of this type of group gets into the guts of handloading and into fine tuning load development.

In order to assess whether or not a given shot is kept or thrown out, the criterion we use is: if the shot was called BAD at the moment of shooting (BEFORE the target is examined), the shot can be thrown out; if not, the shot is kept, no matter how 'wild' it appears to be. In other words, if the shooter knows he made an error, we don't keep the shot if testing load performance.

Large x average, small r standard deviation

this group may simply be due to a constant side wind effect; however, there may also be a barrel vibration or bullet stabilization effect. Adjustment of the sites to ``zero'' the firearm may only correct the symptom, not the cause. That is, you may obtain a zero at one range-to-target, but find the group impacts right or left at other ranges. Such zero-ing is fine for fixed range target shooters, but may not be acceptable when variable ranges are possible. If multiple range precision is important, it is far better to properly tune the load than merely move the sites around to give the false sense of a zero'd rifle.

Large y average, small r standard deviation

the velocity or deceleration characteristics may not be their theoretical values. See comments under 'large x average, small r standard deviation' for additional discussion.

r range

this is a very interesting statistic that contains much information about the combined barrel vibrations and bullet stabilization effects. For small such effects, the r range should be approximately 1/2 the center-to-center group size, average r will be approximately zero and all x and y statistics will be nearly the same. If you draw a circle with the center at the point of aim and radius of r range, shot impacts will be randomly scattered within the circle.

On the other hand, either a large barrel vibration or bullet stabilization effect may cause the r range to be small while while the center-to-center group size is large.

In order to see these effects, larger groups and data sets are necessary. For example, you may wish to shoot 10-20 round groups at a range that gives about a six inch pattern. If the groups result in a small r range (relative to the center-to-center group size), there may be a vibration or stabilization effect, and the groups might appear as a 'donut' around the point of aim.

multiple range-to-target experiments

as a final general example, the graph of standard deviation (x,y and r should all be examined separately) versus range-to-target should be a straight line. A sharp change in the slope of the line may indicate the approximate range a stabilization effect becomes important. It should be noted that the graph will never intercept the standard deviation axis at a value smaller than the offset from linearity caused by the duration of instability.