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The following set of tips are things that are most worth remembering about specific content issues in statistics These are things that have been consistent over the years of the reading This list is not exhaustive! The examples, exercises, and solutions that appear in this book are illustrative of the manner in which you are expected to answer free-response problems, but this list is just a sampling of some of the most important things you need to remember 1 2 3 4 When asked to describe a one-variable data set, always discuss shape, center, and spread Understand how skewness can be used to differentiate between the mean and the median Know how transformations of a data set affect summary statistics Be careful when using normal as an adjective Normal refers to a specific distribution, not the general shape of a graph of a data set.

Reverse Address Resolution Protocol (RARP)

12:

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It s better to use approximately normal, mound-shaped, bell-shaped, etc, instead You will be docked for saying something like, The shape of the data set is normal Remember that a correlation does not necessarily imply a real association between two variables (correlation is not causation) Conversely, the absence of a strong correlation does not mean there is no relationship (it might not be linear) Be able to use a residual plot to help determine if a linear model for a data set is appropriate Be able to explain your reasoning Be able to interpret, in context, the slope and y-intercept of a least-squares regression line Be able to read computer regression output Know the definition of a simple random sample (SRS) Be able to design an experiment using a completely randomized design Understand that an experiment that utilizes blocking cannot, by definition, be a completely randomized design.

Know the difference between the purposes of randomization and blocking Know what blinding and confounding variables are Know how to create a simulation for a probability problem Be clear on the distinction between independent events and mutually exclusive events (and why mutually exclusive events can t be independent) Be able to find the mean and standard deviation of a discrete random variable Recognize binomial and geometric situations Never forget that hypotheses are always about parameters, never about statistics Any inference procedure involves four steps Know what they are and that they must always be there And never forget that your conclusion in context (Step 4) must be linked to Step 3 in some way When doing inference problems, remember that you must show that the conditions necessary to do the procedure you are doing are present It is not sufficient to simply declare them present..

14. The next workflow activity to insert is an instance of the IfElse activity. Drag this onto the designer s surface, and drop it below the Code activity you just placed.

The use of a protocol analyzer can spot security risks in real time, identify network problems efficiently, and reduce network operating costs. An existing protocol analyzer used for wired LANs can be equipped with an 802.11b (2.4 GHz) or 802.11a (5 GHz) radio card and software to function in the wireless environment. Network Instruments offers 802.11b and 802.11a wireless support in its Observer line of network monitor and protocol analyzers. In addition to wireless troubleshooting tools, Observer offers a number of security and intrusion-detection facilities, including the ability to alert administrators when unauthorized users try to gain access to the WLAN, improper WEP usage, and exposure of rogue APs. The fact that these features, full wireless and wired troubleshooting, are combined into one unit makes it easier to isolate problems. Among the capabilities of Observer is that it identifies errors on the WLAN by station (see Figure 8-2) and aggregates signal measurements. It measures wireless speeds as well as signal strength by station. It also takes AP statistics (see Figure 8-3). In AP statistics mode, Observer shows traffic passing through any AP, displaying the following

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