Homework 6
Answer the following questions: (10 point each)
1- Consider the traffic accident data set shown in Table below.
Traffic accident data set.
Weather Condition
Driver’s
Condition
Traffic Violation
Seat Belt
Crash
Severity
Good
Bad
Good
Bad
Bad
Bad
Bad
Good
Good
Bad
Good
Bad
Alcohol-impaired
Sober
Sober
Alcohol-impaired
Alcohol-impaired
Alcohol-impaired
Alcohol-impaired
Sober
Alcohol-impaired
Sober
Alcohol-impaired
Sober
Exceed speed limit
None
Disobey stop sign
Exceed speed limit
Disobey traffic signal
Disobey stop sign
None
Disobey traffic signal
None
None
Exceed speed limit
Disobey stop sign
No
Yes
No
Yes
No
Yes
Yes
Yes
No
Yes
Yes
Yes
Major
Minor
Minor
Major
Major
Minor
Major
Minor
Minor
Major
Major
Minor
a. Show a binarized version of the data set.
Answer:
b. What is the maximum width of each transaction in the binarized data?
Answer:
c. Assuming that support threshold is 30%, how many candidate and frequent item sets will be generated?
2- Consider the data set shown in Table below. The first attribute is continuous, while the remaining two attributes are asymmetric binary. A rule is considered to be strong if its support exceeds 15% and its confidence exceeds 60%. The data given in Table below supports the following two strong rules:
(i) {(1 ≤ A ≤ 2), B = 1} → {C = 1}
(ii) {(5 ≤ A ≤ 8), B = 1} → {C = 1}
A
B
C
1
2
3
4
5
6
7
8
9
10
11
12
1
1
1
1
1
0
0
1
0
0
0
0
1
1
0
0
1
1
0
1
0
0
0
1
a. Compute the support and confidence for both rules.
Answer:
S ({(1 ≤ A ≤ 2), B = 1} → {C = 1}) =
C ({(1 ≤ A ≤ 2), B = 1} → {C = 0}) =
S ({(5 ≤ A ≤ 9), B = 1} → {C = 1}) =
C ({(5 ≤ A ≤ 9), B = 1} → {C = 1}) =
3. Consider the data set shown in Table below. Suppose we are interested in extracting the following association rule:
{α1 ≤ Age ≤ α2, Play Piano = Yes} → {Enjoy Classical Music = Yes}
Age
Play Piano
Enjoy Classical Music
9
11
14
17
19
21
25
29
33
39
41
47
Yes
Yes
Yes
Yes
Yes
No
No
Yes
Yes
Yes
No
No
Yes
Yes
No
No
Yes
No
No
No
No
Yes
Yes
Yes
To handle the continuous attribute, we apply the equal-frequency approach with 3, 4, and 6 intervals. Categorical attributes are handled by introducing as many new asymmetric binary attributes as the number of categorical values. Assume that the support threshold is 10% and the confidence threshold is 70%.
(a) Suppose we discretize the Age attribute into 3 equal-frequency intervals. Find a pair of values for α1 and α2 that satisfy the minimum support and minimum confidence requirements.
Answer:
(b) Repeat part (a) by discretizing the Age attribute into 4 equal-frequency intervals. Compare the extracted rules against the ones you had obtained in part (a).
Answer:
(c) Repeat part (a) by discretizing the Age attribute into 6 equal-frequency intervals. Compare the extracted rules against the ones you had obtained in part (a).
Answer:
4. For each of the sequence w = <e1, . . . , elast> below, determine whether they are subsequences of the following data sequence:
<{A, B}{C, D}{A, B}{C, D}{A, B}{C, D}>
subjected to the following timing constraints:
mingap = 0 (interval between last event in ei and first event in ei+1 is > 0)
maxgap = 2 (interval between first event in ei and last event in ei+1 is ≤ 2)
maxspan = 6 (interval between first event in e1 and last event in elast is ≤ 6)
ws = 1 (time between first and last events in ei is ≤ 1)
a. w = < {A}{B}{C}{D}> Answer:
b. w = < {A} {B, C, D} {A}> Answer:
c. w = < {A} {B, C, D} {A}> Answer:
d. w = < {B, C} {A, D} {B, C}> Answer:
e. w = < {A, B, C, D} {A, B, C, D}> Answer:
5. Draw all candidate subgraphs obtained from joining the pair of graphs shown in Figure below Assume the edge-growing method is used to expand the subgraphs.
Answer:
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Homework 45
/in Uncategorized /by developerHomework
Cases: Read the assigned cases below, and answer the corresponding questions to each case in no more than one page per case, unless otherwise indicated.
InnoMedia
Catfish Canoe
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Homework 5 Gas Permeability Name Darcy S Law For Gas Permeability Measurements P
/in Uncategorized /by developerNeed help answering these questions. Any help would be great..
Thank you in advance
Homework 5: Gas PermeabilityName:Darcy’s Law for Gas Permeability Measurementsp’ form (for gases, esp. at low p):(go at some p "base", P. .KA (p? – P2Usually, P2 =1 atm = P.qb2ul Pband q, is usually measured at pz =1 atm = Ppq form (for gases, esp. at low p):( q evaluated at P = Pavg =(P1+ p2)/2)q = Ka (p, – P2)Note:q . P =q. Ps, thus q =q. P./PAll of these forms require a suitable conversion constant unless Darcy units are used1. Briefly explain why the liquid form of Darcy’s law does not work for gases (esp. at low pressures). Hint:What is the definition of q? Is q constant for a gas throughout the core? Why or why not? If q is not constant,what is constant for a gas throughout the core? At high pressures, e.g. at pi = 3000 psi and p2 = 2900 psi, whatpercent will q change from the inlet to the outlet of the core? (Use the back or other paper if you need moreroom.)2. Given the following lab data for an air permeability measurement test (A = 3.2 cm?, L = 2.8 cm, (calculate Hfrom the correlation below, lab temp = 70 F), pi = 4 atm, p2 = 1 atm, flow of 945 cm’ of air (at 1 atm at 60 F)in 3 minutes), determine the core’s permeability in this direction using:(a) The q bar (at p) equation [ 11.0 md ](b) The p’ equation [ 11.0 md ]For air viscosity, use correlation of Mason and Monchick (1965):Hair =(1717 + 4.8T)x10’s cp (where T is in *C)
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Homework 5 Part A
/in Uncategorized /by developerHomework 5 (part a): 40 pointsFind the first and second principal components for the following data set following steps 1through 4 given on the paper “A tutorial on Principal Components Analysis” by Lindsay I Smith.What is the percentage of variance explained by each principal components? Plot the twoprincipal components along with the mean subtracted data you get in step 2.
Note: Please calculate the value of eigenvalue and eigenvector in step 4 manually by hand. For other steps, you ‘can’ use Excel or MATLAB but it is not mandatory.
I’ve attached the data points
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Homework 5 Pols 3316 1 A Researcher Is Trying To Study What Factors Make A Perso
/in Uncategorized /by developerHaving some trouble solving this question. Any help is appreciated.
Homework 5: Pols 33161 . A researcher is trying to study what factors make a person more approving of Donald Trump duringthe Republican primary campaign . She uses the approval of Trump question from the 2016 NES pilotstudy ( fttrump ) . It ranks feelings for Trump on a scale from O ( completely dislike ) to 100 ( completelylike ) .The first variable she uses a person’s age . The regression results are pictured below . Answer thefollowing questions about these results .Linear RegressionModel SummaryModelRR =Adjusted RX =RAISE0. 1730.0300.02935.99ANOVA10ModelSum of SquaresMean Square7Regression478114781736.915. 001Residual1.548 8 + 6)11951295Total1.596 0 + 51996CoefficientsStandardizedaMode!UnstandardizedStandard Error1( Intercept )20.4733. 1266.550<. 001age0. 3720. 06*0 . 1736. 075<. 001A . What is the effect of a 1 year increase in the respondent’s age on approval for Trump ? What is theeffect of a 10 year increase in a person’s age ? For a respondent who is 30 years old , what is theexpected score they would give Trump ?"B . What is the standard error of the effect of a person’s age ? What is the p- value ? Is this statisticallysignificant at the 0 . 05 level ( two-tailed ) ? How do you know ?C . What is the R- squared value ? What does this mean ?"
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Homework 5 Risk Determination Decision Tree Analysis1 Review Module 5 Lecture No
/in Uncategorized /by developerHomework # 5 Risk Determination & Decision Tree Analysis
1. Review Module-5 Lecture Notes and Chapter Readings
2. Use the Risk Determination Excel Workbook and complete the following worksheets:
a. Corporate Assets Risk Summary – Tab (25-Points)
i. Use the Reference Tab in the workbook to select the appropriate values from the respective tables and complete Columns C, D, E, F, & G (Hint: use the Threat Vulnerability Reference Table; return the numerical value for the corresponding probability and impact).
Threat Vulnerability Work Table
Impact
Low
Medium
High
Probability
High
3
6
9
Medium
2
5
8
Low
1
4
7
ii. Column H (Risk Score) is a calculated field already formatted
iii. Column I (Possible Safeguards) provide the safeguards you would put in place to mitigate the threat (e.g., controls, policies, etc.); provide sufficient level of detail
iv. Column J (Cost Estimates) provide cost estimates/ranges for the safeguards you would put in place to mitigate the threat; provide sufficient level of detail in the Comments Section Column K.
v. Provide thorough summary analysis of each section
b. Occupation Analysis – Tab (25-Points)
i. Use the Risk Level Table provided on worksheet (Cells B25-C31) to assign the appropriate value for each occupation and the corresponding threats outlined in Columns C,D,E,& F
ii. Column G (Total) is a calculated filed already formatted
iii. Complete the occupational analysis; answer the four questions after completing your occupational vulnerability assessment; provide sufficient level of detail in your responses.
c. Decision Tree Analysis – Tab (50-Points)
i. Examine the Decision Tree Analysis for enterprise CRM solution approach
ii. Complete the corresponding tables for both paths and individual branches referencing the values in the decision tree diagram.
iii. Some of the data is already populated
iv. Total fields, Branch Total fields, and Value Fields are calculated fields and are already formatted
v. Answer the question regarding which options provides the best overall value
vi. Explain your reasoning for the choice you made, response should be based on your analysis of the decision tree results.
vii. Hint: Only one of the value fields should have a negative value when finished
3. Complete the Risk Determination Worksheets (M.S. Excel Document not PDF) and upload the file using the designated link on Moodle on or before the assignment due date.
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Homework 6 3 Using The Same Approach We Used For The Unsorted Circular List Crea
/in Uncategorized /by developerDesign, implement, and test a soubly linked list ADT, using DLLNode objects as the nodes. In addition to our standard list operations, your class should provide for backward iteration through the list. To support this operation , it should export a resetBack method and a getPrevious method. To facilate this, you may want to include an instance variable last than always re ferences the last element on the list
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Homework 6 Answer The Following Questions 10 Point Each 1 Consider The Traffic
/in Uncategorized /by developerHomework 6
Answer the following questions: (10 point each)
1- Consider the traffic accident data set shown in Table below.
Traffic accident data set.
Weather Condition
Driver’s
Condition
Traffic Violation
Seat Belt
Crash
Severity
Good
Bad
Good
Bad
Bad
Bad
Bad
Good
Good
Bad
Good
Bad
Alcohol-impaired
Sober
Sober
Alcohol-impaired
Alcohol-impaired
Alcohol-impaired
Alcohol-impaired
Sober
Alcohol-impaired
Sober
Alcohol-impaired
Sober
Exceed speed limit
None
Disobey stop sign
Exceed speed limit
Disobey traffic signal
Disobey stop sign
None
Disobey traffic signal
None
None
Exceed speed limit
Disobey stop sign
No
Yes
No
Yes
No
Yes
Yes
Yes
No
Yes
Yes
Yes
Major
Minor
Minor
Major
Major
Minor
Major
Minor
Minor
Major
Major
Minor
a. Show a binarized version of the data set.
Answer:
b. What is the maximum width of each transaction in the binarized data?
Answer:
c. Assuming that support threshold is 30%, how many candidate and frequent item sets will be generated?
2- Consider the data set shown in Table below. The first attribute is continuous, while the remaining two attributes are asymmetric binary. A rule is considered to be strong if its support exceeds 15% and its confidence exceeds 60%. The data given in Table below supports the following two strong rules:
(i) {(1 ≤ A ≤ 2), B = 1} → {C = 1}
(ii) {(5 ≤ A ≤ 8), B = 1} → {C = 1}
A
B
C
1
2
3
4
5
6
7
8
9
10
11
12
1
1
1
1
1
0
0
1
0
0
0
0
1
1
0
0
1
1
0
1
0
0
0
1
a. Compute the support and confidence for both rules.
Answer:
S ({(1 ≤ A ≤ 2), B = 1} → {C = 1}) =
C ({(1 ≤ A ≤ 2), B = 1} → {C = 0}) =
S ({(5 ≤ A ≤ 9), B = 1} → {C = 1}) =
C ({(5 ≤ A ≤ 9), B = 1} → {C = 1}) =
3. Consider the data set shown in Table below. Suppose we are interested in extracting the following association rule:
{α1 ≤ Age ≤ α2, Play Piano = Yes} → {Enjoy Classical Music = Yes}
Age
Play Piano
Enjoy Classical Music
9
11
14
17
19
21
25
29
33
39
41
47
Yes
Yes
Yes
Yes
Yes
No
No
Yes
Yes
Yes
No
No
Yes
Yes
No
No
Yes
No
No
No
No
Yes
Yes
Yes
To handle the continuous attribute, we apply the equal-frequency approach with 3, 4, and 6 intervals. Categorical attributes are handled by introducing as many new asymmetric binary attributes as the number of categorical values. Assume that the support threshold is 10% and the confidence threshold is 70%.
(a) Suppose we discretize the Age attribute into 3 equal-frequency intervals. Find a pair of values for α1 and α2 that satisfy the minimum support and minimum confidence requirements.
Answer:
(b) Repeat part (a) by discretizing the Age attribute into 4 equal-frequency intervals. Compare the extracted rules against the ones you had obtained in part (a).
Answer:
(c) Repeat part (a) by discretizing the Age attribute into 6 equal-frequency intervals. Compare the extracted rules against the ones you had obtained in part (a).
Answer:
4. For each of the sequence w = <e1, . . . , elast> below, determine whether they are subsequences of the following data sequence:
<{A, B}{C, D}{A, B}{C, D}{A, B}{C, D}>
subjected to the following timing constraints:
mingap = 0 (interval between last event in ei and first event in ei+1 is > 0)
maxgap = 2 (interval between first event in ei and last event in ei+1 is ≤ 2)
maxspan = 6 (interval between first event in e1 and last event in elast is ≤ 6)
ws = 1 (time between first and last events in ei is ≤ 1)
a. w = < {A}{B}{C}{D}> Answer:
b. w = < {A} {B, C, D} {A}> Answer:
c. w = < {A} {B, C, D} {A}> Answer:
d. w = < {B, C} {A, D} {B, C}> Answer:
e. w = < {A, B, C, D} {A, B, C, D}> Answer:
5. Draw all candidate subgraphs obtained from joining the pair of graphs shown in Figure below Assume the edge-growing method is used to expand the subgraphs.
Answer:
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Homework 6 Ecn 100 Dear Ecn 100 Using The Quite Reasonable Assumption That The M
/in Uncategorized /by developer(1)Marginal revenue is the addition to a firm’s total revenue when the firm produces one additional unit of output and sells this unit of output at the market price. Knowing that MR = dTR/dq, prove that the marginal revenue to the firm is usually below but at under specific conditions equal to the average revenue (AR) of the firm.(2)Given your answer in (1) above, what must we know about the price elasticity of demand on the demand curve when a firm lowers in price in order for total revenue (TR) to rise, pretty much stay the same, or fall?(3)What is meant my atomaticity in a market? In a market where atomaticity exists, what does this means for the price elasticity of demand facing a firm. What is the shape of thedemand curve facing this firm? What does this mean for the relationship between MR, AR, and P at the profit maximizing point of production for the firm?(4)Your firm faces a short run average cost curve SRAS that has an average cost per unit of output at $6.00 at its minimum point. Your firm faces a demand curve that falls below the minimum point of the SRAS. What should the firm do in the short run? If the firm follows your advice in the short run, what is the firm maximizing or minimizing? If the demand curve remains where it is, what should the firm do in the long run? In the REAL WORLD, if in the long run, the firm wants to be successful, what two main choices does it have?(5)Why is the marginal cost curve the supply curve for a firm that maximizes it profits? Explain your answer with a graph. Show the areas of profits for any price that the firm may face.(6)Let’s pretend that you are in the shelter-building business. You construct dwellings for people in your community.However, you are losing money in your business. You are in the short run. You are able to determine your cost schedule (SRAC and SRMC curves) as well as the demand function that you face. Draw your current situation on a graph.You decide that you want to stay in the shelter business as you wait for the long run. What must happen on your graph to make this possible and how do you intend do go about changing the conditions shown by your graph.(7)Now, from (6) above, assume that in the shelter-building business, you use capital and labor (your time, effort, mind-power, etc.) to produce your shelters. Your cost curves from (6) employ a cost-minimizing strategy. You build five shelters a month. Draw an isoquant diagram that illustrates where you are in the SR money-losing situation. So, according to your diagram, you could do better cost-wise and still be able to build the five monthly shelters. What condition(s) have to be met for you to be sure that you are truly minimizing your costs of production at the rate of 5 shelters per month?As you move into the long-run (LR), assume that you are indeed successful in remaining in business. How might you show the achievement of this success on your isoquant diagram?(8)When the demand curve facing a firm shows a willingness to pay that is always less that the average cost of output, what should the firm do in the SR? If this situation does not change in the LR, what should the firm do?(9)If a firm strives to maximize profits, is a price taker in both the product and factor markets, and is hiring labor and capital as factors of production, what rule must it follow with respect to the cost and productivity of the two factors AT THE MARGIN?How would you show this as a proof? HINT: Begin with – profits – TR – TC.(10)As a shelter-builder, you want to make more money in order to buy more stuff for your leisure time (digital cameras, iPhone 5, designer jeans, etc.). So, you lower your price of individual shelters from $1000 to $950. At this point in time, the price elasticity of demand that you face is (-) 1.04. Was this a good move for you? Now, what if you had been selling 30 shelters per month at the old price and now 31 shelters per month at the new price? What does this say about the price elasticity of demand and whether or not your price drop strategy was correct?(11)You face a demand curve that is – q = 20 – p.Calculate the marginal revenue curve.Assume that you face a constant returns to scale production function and your MC = $5.00.Draw a graph showing the demand curve the MR curve and the cost curves. (AC and MC).Now, you are able to produce an output, “x” that maximizes your profits. Calculate your profits.(12)In (11) you reduce your constant returns to scale costs by $1.00. You cut your AC by $1.00. What are profits when maximized?
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Homework 7 Assume That The Logic Blocks Needed To Implement A Processor S Datapa
/in Uncategorized /by developerFor Data organization and architecture homework: Please explain if possible question 1 through 8. I really appreciate the explanations
Homework 7 Assume that the logic blocks needed to implement a processor’s datapath have the followinglatencies: 200p§ 70m 20p§ 90p§ 909s 250p§ 15gb; lORs 1. If the only thing we need to do in a processor is fetch consecutive instructions, whatwould the cycle time be? 2. Consider a processor that only has one type of instruction: unconditional branch. Whatwould the cycle time for this datapath? 3. Consider a processor that only has one type of instruction: conditional branch. Whatwould the cycle time for this datapath? The coming three questions refer to the datapath element Shift-left-Z: 4. Which kinds of instructions require this resource?5. For which kinds if instructions is this resource on the path? Assume the following latencies for logic blocks in the databath: Immm-“mmmmwmmm 6. What is the clock cycle time if the only type of instructions we need to support are ALUinstructions (add, and, etc.) 7. What is the clock cycle time if we only hayejtg support (by) instructions?8. What is the clock cycle time if we must support (add, peg, lyy, and s35) instructions?
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Homework 7c Total Combined Leverage 1
/in Uncategorized /by developerQuestion 2 (1 point)
Haunted Forest, Inc.is selling fog machines.
Use the following information about Haunted Forest, Inc. to answer the following questions.
Average selling price per unit $316.
Variable cost per unit $218
Units sold 373
Fixed costs $16,349
Interest expense $4,388
Based on the data above, what is the degree of total (combined) leverage of Haunted Forest, Inc.?
Round the answer to two decimals
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