a) Explain what is meant by UBV filters.

b) Explain why astronomers would want to use such filters.

c) Give an example of the usage of UBV filters.

2. Describe ASK, explain how it works and why we use it:

3. Explain what PCM does and how it works:

4. Which of the following networking device(s) block(s) broadcast traffic, thus dividing networks into separate subnets? (Hint: only OSI Network layer devices can divide networks into separate subnets): Routers, Switches, Wireless Access Points (bridges)

5. List the three types of multiplexing from the text and explain how they work:

. List two network layer protocols and explain what they do:

6. Explain what the acronym “ARQ” stands for and explain how it works:

7. The Session and Presentation layers are explicit layers in the OSI model, but are embedded within the Application layer of the TCP/IP protocol stack. Explain what the Session and Presentation layers do.

Session:    

Presentation:    

8. How does the application layer handle security?

Please DO NOT HANDWRITE

1. Immediately after a ban on using hand-held cell phones while driving was implemented, compliance with the law was measured. A random sample of 1,250 drivers found that 98.9% were in compliance. A year after the implementation, compliance was again measured to see if compliance was the same (or not) as previously measured. A different random sample of 1,100 drivers found 96.9% compliance.

1. State an appropriate null and alternative hypothesis for testing whether or not there is any statistical difference (i.e., a two-sided test) in these two proportions measured initially and then one year later.
2. Conduct the test of hypothesis using a significance level of α= 0.05. Be sure to check the assumptions and conditions for your test. State the P-value of your test and also state your conclusion.  
3. Develop a 95% confidence interval for the true difference in proportions between the first survey and the second survey and explain what this confidence interval means in context of this problem.  

Use SPSS to follow the steps below and conduct a simple linear regression of the following data:

1. State your hypotheses (e.g. HA: “calories will significantly predict sodium”)

2. Create a scatterplot of the data. State if the scatterplot appears to contain a linear relationship.

3. Conduct the analysis in SPSS. Include all of the important outputs (e.g. ANOVA Table, Coefficient Table, Regression Table).

4. State your conclusion regarding the null hypothesis.

5. Write your conclusion. Include: (i) if there is a significant relationship between calories and sodium, based on the coefficient/slope, and (ii) if the model significantly predicts the sodium level, based upon adjusted R- squared.

6.

Use the results above to create the regression line equation (e.g. Yi = β1Xi + β0).

1. What numerical value is the slope (β1) associated with calories (Xi)?

2. What numerical value is the y-intercept (β0) associated with the regression line equation?

3. Write your regression line equation inserting the numerical slope value and y-intercept value (e.g. Yi = 0.75*Xi + 1.23)

4. Using the regression line equation from problem 5:

   1. What value is the (predicated) Yi, when Xi = 180?

   2. What value is the (predicated) Yi, when Xi = 155?

   3. What value is the (predicated) Yi, when Xi = 199?

The first excited state of Ca²⁺ is assed with 422.7 nm light. The degeneracy ratio g^*/g₀ =3

a ) Use the Boltzmann distribution to calculate the relative population of Ca in the ground and the excited state ie the ration N^*/N_o at

(i)             2500k                         (ii)       6000k   

(b) A student wishes to collect a florescence emission spectrum. They are using the narrow slits for the excitation monochrometer and broad slits for the emission monochrometer. Explain why that is counter-productive?

Joint cost allocation

Rosie’s Roses produces three colors of roses: red, white, and peach. The roses are produced jointly in the same garden, and aggregately cost a total of $110 per harvest. One harvest produces 80 red roses, 70 white roses, and 50 peach roses. Rosie also noted that the peach roses require a fertilizer that is twice as expensive as the fertilizer required by the white and red roses. However, due to the structure of the shared garden space, the more expensive fertilizer is used for all flower types in a joint production process.

1. Using the physical units method, allocate the joint costs of production to each product. Round your answers to two decimal places.

2. Using the weighted average method, allocate the joint costs of production to each product. Round your answers to two decimal places.

3. Is the cost of the type of fertilizer required by each type of rose a good weight factor?

The cost of the type of fertilizer required by each type of rose may be a good weight factor, if fertilizer is   cost of the joint production process.

To analyze how well lie detectors perform when subjects are stressed, 48 randomly chosen
subjects were connected to a lie detector and asked to read true statements out loud while
receiving an electric shock. The lie detector incorrectly reported that 27 of the 48 participants
were lying.
Note: For this problem, you will have to enter the counts directly into StatKey. Do not use
any of the book’s available datasets to answer the following questions!

(a) Use StatKey to determine the best estimate, based on this data, of the proportion of times
the lie detector yields false positives, i.e., inaccurately reports deception.
(b) Use StatKey to create 5000 bootstrap samples and a bootstrap distribution of sample
proportions. What are the center and standard error of your bootstrap distribution?
(c) Use StatKey and your bootstrap distribution to find a 95% confidence interval for the
overall percentage of false positives reported by the lie detector. What is the margin of
error?
(d) Does this sample provide evidence that lie detectors give inaccurate results more than half
the time when subjects are stressed? State the relevant null and alternative hypotheses,
use StatKey to create a randomization distribution based on this sample and H0, obtain
the p-value, and state your conclusion clearly.

The cells accumulate neutral red (pKa=7), their lysosomes swell-up to many times their normal size. The swelling cannot be accounted for simply by the mass of accumulated neutral red. Can you suggest what else may contribute to the swelling and why it occurs?

A bucket contains exactly 3 marble, one red, one blue and one green.

A person arbitrarily pulls out each marble one at a time.

What is the probability that the last marble removed is non-red?

Answer in the form of a fully reduced fraction.