FATHOM is a fast paced action-strategy submarine combat game for the PC, where you’ll need quick reflexes, clever piloting skills, and tactical leadership to survive. Bringing a unique mixture of First-Person-Shooter (FPS) and Real-Time-Strategy (RTS) genres, FATHOM is a multi-player focused game that offers a variety of modes that support competitive (1v1 and team) play, as well as cooperative play. Take control of a Deep Submergence Vehicle (DSV) and prepare for battle. Use beacons to call down structures from the sea surface and layout your base of operations to begin your campaign. Construct warships and command your fleet into the heart of your enemy’s base! Set up blockades of deployable turrets and mines to defend strategic locations from your enemies.

• Fathom 2 Mac

Call to the sea surface for depth charge bombardments from above or bring huge capital ships to bear in an all-out epic war beneath the waves! Working on a new map, 'The pit' (until I can think of a better name). Devin got the UI switched to the new Unity solution and I've started the graphics for the final HUD.

Theres a new loading screen with a map preview and progress bar and a few new sounds and effects. We are going to start experimenting with the Steam API in the next week or so.

I think Devin is pretty close to having the code finalized for a demo. Just waiting on the slacker art guy after that. The new Oculus Rift stuff is in and working well also. Like our facebook page for a chance to play the alpha with the devs! Let us know what you think about the game so far and ask us some questions! Till next week!

Fathom: Two variable analysis, Normal distributions MDM4U: Exploring the Normal Distribution with Fathom In this exercise, you will learn the basic features of Fathom, and use Fathom to: 1 ) Plot the normal curve over the historgram 2) Generate a normally distributed set of data in Fathom 3) Apply the normal distribution model to some real data 1. If you roll a pair of dice 100 times, and record the sum of the dice, what type of distribution will results?

We can simulate this in Fathom as follows: i) Create a collection of dice rolls. Make a new collection, and add two attributes called die1 and die2.

For each of these attributes, enter the formula randomInteger(1,6). This will generate a random value between 1 and 6, simulating a dice roll. Add another attribute called sum, and enter the formula die1 + die2. Create 100 cases (right mouse click, New Cases) ii) Create a histogram of the sum of the dice. You can quickly re-generate a completely new set of random values, and watch the histogram change dynamically (right mouse click, Rerandomize) iii) Superimpose the normal curve on top of the histogram. Change the scale of the vertical axis to show relative frequencies instead of count. From the Graph menu, choose Scale- Density.

(This sets the graph to a show relative frequencies). Plot the normal function by choosing Plot Function, and entering the formula: normalDensity(x,mean,stdDev).

Plot the following values:. mean.

Fathom 2 Mac

median. mean-stdDev and mean+stdDev 2. What if you had more dice with more sides? Would the distribution be similar? Modify your collection to find out, and plot the resuluts.

Explore the Average Income data from the 2001 Canadian Census. This data is the average income of all working people over the age of 15 for 299 different census regions.

Create a historgram of the data, and comment on the overall distribution. Is the distribution fairly normal? Justify your conclusion.

Assuming that the distribution is normal, what percentage of municipalities would you expect to have an income below $22,000? Does the actual data match your prediction?