Compare the variable types which can be depicted i a probability versus a Poisson distribution

Compare the variable types which can be depicted in a probability versus a Poisson distribution. The Poisson distribution studies a series of events where the average time between events is a known, but the exact timing of such events is unknown or random. The probability is a measure of the chance an occurrence or event will occur but in a randomized study. 0 would imply completely impossible, where as, I would suggest certainty. 00 .01 .02 .03 .04 .05 .06 -07 08 0.0 5000 .5040 5080 .5120 .5160 5199 5239 5279 .5319 0.1 .5398 5438 5478 5517 5557 .5596 5636 .5675 5714 5753 0.2 5793 .5832 .5871 5910 5948 5987 6026 6064 .6103 .6141 0.3 6179 .6217 .6255 6293 6331 6368 6406 6443 .6480 6517 0.4 .6554 -6591 6628 6664 .6700 .6736 .6772 .6808 .6844 6879 0.5 6915 6950 6985 7019 .7054 .7088 .7123 7157 .7190 7224 0.6 .7257 .7291 .7324 .7357 7389 .7422 7454 .7486 .7517 .7549 0.7 7580 7611 .7642 7673 .7704 .7734 .7764 .7794 .7823 .7852 0.8 7881 .7910 .7939 7967 .7995 .8023 .8051 8078 .8106 .8133 0.9 .8159 .8186 8212 .8238 8264 8289 8315 .8340 8365 8389 1.0 8413 8438 .8461 .8485 .8508 8531 .8554 .8577 .8599 .8621 1.1 .8643 8665 .8686 8708 8729 8749 8770 .8790 .8810 .8830 1.2 8849 8869 8888 8907 .8925 .8944 8962 .8980 .8997 9015 1.3 9032 9049 .9066 9082 .9099 .9115 9131 9147 9162 9177 1.4 9192 .9207 9222 .9236 .9251 .9265 .9279 .9292 .9306 9319 1.5 9332 9345 .9357 .9370 9382 9394 9406 .9418 9429 9441 1.6 .9452 9463 .9474 .9484 9495 9505 .9515 9525 9535 9545 1.7 .9554 .9564 9573 9582 9591 .9599 9608 .9616 9625 9633 0641 9640 0656 0671 9678 .9686 .9693 .9699 -9706