Computer Science

using excel Project Instructions: The project consists of 4 problems and a summary set of questions. For each problem, tom hints and theoretical background is provided. In the following set of problems, r is the standard uniform random value (a continuous random value between 0 and 1). Problem 1 Generate 1000 random values r. For each r generated, calculate the random value ???? by: ???? = ?????????(????), where “Ln“ is the natural logarithm function. Investigate the probability distribution of X by doing the following: 1. Create a relative frequency histogram of X. 2. Select a probability distribution that, in your judgement, is the best fit for X. 3. Support your assertion above by creating a probability plot for X. 4. Support your assertion above by performing a Chi-squared test of best fit with a 0.05 level of significance. 5. In the word document, describe your methodologies and conclusions. 6. In the word document, explain what you have learned from this experiment. Hints and Theoretical Background A popular method for generating random values according to a certain probability distribution is to use the inverse transform method. In this method, the cumulative function of the distribution (F(x)) is used for such a random number generation. More specifically, a standard uniform random value r is generated first. Most software environments are capable of generating such a value. In Excel and R, functions “=RAND()” and “runif()” generate such a value respectively. After r has been created, it then replaces F(x) in the expression of the cumulative function and the resulting equation is solved for the variable x. For example, suppose we wish to generate a random value according to the exponential distribution with a certain mean (say ?). The cumulative function for the exponential distribution is: ????(????) = ???? ? ???? ? ???? ???? ???? (The quantity 1/? in the above description is called the rate of the exponential random variable and is denoted by ?.) Therefore, to generate a random value x that belongs to the exponential distribution with a mean of ?. We first generate a standard uniform value r, then replace F(x) by r in the above expression, and solve the resulting equation for the variable x: ???? = ???? ? ???? ? ???? ???? ???? ???? ? ???? ???? ???? = ???? ? ???? ? ???? ???? ???? = ????????(???? ? ????) ???? = ????? ????????(???? ? ????) The formula above means that if R is a standard uniform random variable, then the random variable X obtained by the expression ???? = ????? ????????(???? ? ????) will belong to the exponential distribution with an average which is equal to the value of ?. This formula can be simplified as: ???? = ????? ????????(????) (Note that If R is a standard uniform random variable, then (1 ? ????) is also standard uniform.) A special case of the above formula is when ???? = ????. This means that a random variable x generated by the formula ???? = ?????????(????)is an exponential random variable with an average of 1 (or, rate=1). Problem 2 Generate three sets of standard uniform random values, ????????, ????????and ????????, each consisting of 10,000 values. Next, calculate the random value x according to the following formula: ???? = ?????????(????????????????????????). Investigate the probability distribution of X by doing the following: 1. Create a relative frequency histogram of X. 2. Select a probability distribution that, in your judgement, is the best fit for X. 3. Support your assertion above by creating a probability plot for X. 4. Support your assertion above by performing a Chi-squared test of best fit with a 0.05 level of significance. 5. In the word document, describe your methodologies and conclusions. 6. In the word document, explain what you have learned from this experiment. Hints and Theoretical Background: This problem is related to a theorem in the probability theory. The theorem states that: If ????????, ????????, … , ????????are n identical and independent exponential random variables each with a mean of ?, then the random variable obtained by their sum, that is ???????? + ???????? + … + ????????, will have a ????????????????????(????, ????) probability distribution, where n is the shape parameter of the Gamma distribution and ???? = ???? ???????????????? . From the Hints and Theoretical Background of Problem 1, we know that if R is a standard uniform random variable, then ???? = ?????????(????) is an exponential random variable with an average of 1. Therefore, if ???????? , ????????, and ???????? are three independent standard uniform random variables, then ???????? = ?????????(????????)) , ???????? = ?????????(????????), and ???????? = ?????????(????????)are three independent and identical (each with a mean of 1) exponential random variables. Thus, according to the theorem above, the random variable formed by their sum, that is ??????????(????????)? + ??????????(????????)? + (?????????(????????)), will belong to the ????????????????????(????, ????)probability distribution. However algebraically, ??????????(????????)? + ??????????(????????)? + ??????????(????????)? = ??????????(????????) + ????????(????????) + ????????(????????)? = ?????????( ????????????????????????). Therefore, if ???????? , ????????, and ???????? are three independent standard uniform random variables between zero and 1, then the random variable X formed by the formula ???? = ?????????( ????????????????????????) will belong to the ????????????????????(????, ????) probability distribution. Problem 3 Generate a set of 1000 pairs of standard uniform random values ????????and ????????. Then perform the following algorithm for each of these 1000 pairs: Let the output of this algorithm be denoted by Y. Step 1: Generate random values ???????? = ?????????(????????) and ???????? = ?????????(????????) Step 2: Calculate ???? = (?????????????)???? ???? . If ???????? ? ????, then generate a random number ????. If ???? > ????. ???? accept ????????as ????(that is, let ???? = ????????); otherwise if ???? ? ????. ????, else accept ????????? as ???? (that is, let ???? = ?????????). If ???????? < ????, no result is obtained, and the algorithm returns to step 1. This means that the algorithm skips the pair ???????? and ???????? for which ???????? < ???? without generating any result and moves to the next pair ???????? and????????. After repeating the above algorithm 1000 times, a number N of the Y values will be generated. Obviously ???? ? ????????, ???????????? since there will be instances when a pair ???????? and ???????? would not generate any result, and consequently that pair would be wasted. Investigate the probability distribution of ???? by doing the following: 1. Create a relative frequency histogram of ????. 2. Select a probability distribution that, in your judgement, is the best fit for ????. 3. Support your assertion above by creating a probability plot for ????. 4. Support your assertion above by performing a Chi-squared test of best fit with a 0.05 level of significance. 5. In the word document, describe your methodologies and conclusions. 6. In the word document, explain what you have learned from this experiment. Hints and Theoretical Background Other than the inverse transform method used for generating random values that are according to a certain particular probability distribution, a second applied method for generating random values is the Rejection algorithm. The details of this algorithm are explained below: Suppose we wish to generate random values x that is according to a certain probability distribution with ????(????)as its probability density function (pdf). Also suppose that the following two conditions are satisfied (i) we are able to generate random values y that belong to a probability distribution whose probability density function is ????(????), (ii) there exists a positive constant C such that ????(????) ????(????) ? ???? for all y values (this means that the ratio (????(????) ????(????) ) is always bounded and does not grow indefinitely. This condition is almost always satisfied for any two probability density functions ????(????) and ????(????)). The rejection algorithm can now be implemented as follows: Step 1: Generate a random value y that belongs to the probability distribution with ????(????) as its pdf and generate a standard uniform random value r. Step 2: Evaluate ???? = ????(????) ???? ????(????) . If ???? ? ????, then accept y as the random variable x (that is, let ???? = ????); otherwise return to Step1 and try another pair of (???? , ????) values. A few remarks about the Rejection algorithm is worth noting: 1. The probability that the generated y value will be accepted as x, is: ????(????) ???? ????(????) . This is the reason why the algorithm uses a standard uniform value r and accepts y as x if ???? ? ????(????) ???? ????(????) . 2. Each iteration of the algorithm will independently result in an accepted value with a probability equal to: ???? ????? ? ????(????) ???? ????(????) ? = ???? ???? . Therefore, the number of iterations needed to generate one accepted y value follows a geometric probability distribution with mean C. Relevancy of Problem 3 to the Rejection Algorithms: In problem 3, the random variable y , selected from an exponential probability distribution with rate =1 and a pdf of ????(????) = ?????????, is used to first generate the absolute value of a standard normal random variable x (|????|has the pdf: ????(????) = ???? ????????? ????????????? ???? ), and then assign positive or negative signs to this value (through a standard uniform variable r) in order to obtain a standard normal random value. It can be shown algebraically that ????(????) ????(????) = ????????? ???? ???? ? (?????????)???? ???? ? ????????? ???? for all y values (note that ???? ?(?????????)???? ???? ? ???? for all y values). Therefore, the constant C in the assumptions of the algorithm can be chosen to be: ???? = ????????? ???? ? ????. ????????????. Therefore, ????(????) ???? ????(????) = ???? ? (?????????)???? ???? . Hence the following algorithm can be used to generate the absolute value of a standard normal random variable: Step 1: Generate random variables Y and R; with Y being exponential with ????ate=1, and R being uniform on (????, ????) Step 2: If ???? ? ???? ? (?????????)???? ???? , then accept Y as the random variable X (that is, set ???? = ????); otherwise return to Step1 and try another pair of (???? ,????) values. Note that in step 2 of the above algorithm, the condition ???? ? ???? ? (?????????)???? ???? is mathematically equivalent to: ?????????(????) ? (?????????)???? ???? . However, we have already seen in the Hints and Theoretical Backgrounds of the earlier problems that if R is standard uniform, then ?????????(????) is exponential with rate=1. Therefore, the algorithm for generating the absolute value of the standard normal random variable can be modified as follows: Step 1: Generate independent exponential random variables ???????? and ????????; each with ????ate=1. Step 2: Evaluate ???? = (?????????????)???? ???? 2. If ???? ? ????????, then accept ???????? as the random variable X (that is, set ???? = ????????); otherwise return to Step1 and try another pair of (???????? , ????????) values. In fact, it is the above version of the Rejection algorithm that is being implemented in Problem 3. However, in order to obtain a standard normal random value (instead of its absolute value), the step 2 of the above algorithm has been modified as follows: Step 2: Evaluate ???? = (?????????????)???? ???? . If ???? ? ????????, then generate a standard uniform variable R. If ???? ? ????. ????, set ???? = ????????, otherwise set ???? = ?????????. If ???? > ????????, return to step 1 and try another pair of (???????? , ????????) values Note: The standard normal random value generated by the Rejection algorithm can be used to generate any normal random value with a mean ? and a standard deviation ?. Once a standard normal variable Z has been generated, it suffices to evaluate ???? + ???????? to generate the desired normal variable. Problem 4 In the algorithm of problem #3 above, there are instances when the generated random values do not satisfy the condition ???????? ? ???? In order to obtain an acceptable value for ????. In such cases, the algorithm returns to step 1 and generates another two values to check for acceptance. Let ???? be the number of iterations needed to generate ???? of the accepted ???? values (???? ? ????). Let ???? = ???? ???? . (For example, suppose that the algorithm has produced 700 ???? values (???? = ????????????) after 1000 iterations (???? = ????????????????). Then ???? = ???????????????? ???????????? = ????. ????????. This means that it takes the algorithm 1.43 iterations to produce one output. In fact, ???? itself is a random variable. Theoretically, ????(????) – the expected value (i.e., average) of ???? – of an algorithm is a measure of efficiency of that algorithm.) Investigate ???? by the following sequence of exploratory data analytic methods: 1. Estimate the expected value and the standard deviation of ????. 2. Select a probability distribution that, in your judgement, is the best fit for ????. 3. Support your assertion above by performing a Chi-squared test of best fit with a 0.05 level of significance. 4. As the number of iterations ???? becomes larger, the values ???? will approach a certain limiting value. Investigate this limiting value of ???? by completing the following table and plotting ???? versus ????. What value do you propose for the limiting value that ???? approaches to? M W 10 20 30 40 50 60 70 80 90 100 200 300 400 500 600 700 800 900 1000 5. In the word document, communicate to the reader your findings about ????. 6. In the word document, explain what you have learned from this experiment. Summary In the word document, summarize and conceptualize your findings in parts 1 – 4 above by filling the blanks in the sentences below: 1. If ???? is a standard uniform random variable, then ?????????(????) has the ___________________ probability distribution. 2. The sum of three independent and identically distributed _________________ random variables has the ________________________ probability distribution. 3. The output of the algorithm of problem 3 has a ______________________ probability distribution. 4. In step 2 of the algorithm of problem 3, random variables ???????? and ???????? , each of whose probability distribution is ________________________ are used to generate a random value ???? that has the _______________________probability distribution. 5. The random value ???? that was discussed in problem 4, has the ____________________________ probability distribution. The expected value of ???? is: __________.

In this assignment, you will need to run analyses on two data sets from JASP.Part OneFirst, open “Fear of Statistics” as the JASP file from computer. This will still be in the “Descriptives” folder. This will run the descriptive statistics and give you access to the code book. For this part of the assignment, you will need to do the following:Use the codebook reading to explain what the data isInclude a screenshot (Links to an external site.) or picture of the codebookChoose four variables to assessUse the codebook to explain what these four variables are/are described as (e.g., what was being measured?)Don’t worry about the reliability statistics!What is the mean for your four chosen variables? How can we read this in terms of the likert scale? (e.g., how do people feel?)Include a screenshot or picture of the output (software’s analysis) of the descriptive statisticsPart TwoNow, open “Invisibility Cloak” as a JASP file from your computer. This will still be in the “T-Tests” folder. It will run the analyses for you and give you the output. For this part of the assignment, you will need to complete the following:Use the codebook reading to explain what the data isInclude a screenshot (Links to an external site.) or picture of the codebookUse the codebook to explain what the variables in the dataset are/are described as (e.g., what was being measured?)Don’t worry about the assumption checks!Explain the results of the T-Test broadlyWhat is the difference between the means?Why is the result not statistically significant?Why is it important to know what the t-test results areInclude a screenshot or picture of the output of the t-test resultsDescribe the descriptive statisticsMake sure to explain what 0 and 1 areWhat does the difference in the mean indicate? (e.g., what is the average for 0 and the average for 1 and what does this tell us for each variable in the context of what these numbers have been assigned to?)Why might we be concerned with the N in this case?Include a screenshot or picture of the output of the descriptive statistics

You will be expected to execute a short research study on one of three areas that were listed as part of project description. They were intended to be separate research topics. In the end I am looking for a report that will document your research activity that will be done in the format we use for Final Technical Reports. 1. What are the technical challenges for implementing Machine Learning in Size, Weight and Power constrained systems like a smartphone? The desire is to provide computationally and power efficient processing at the edge. Format: ANSIS technical report

Presenting a Physical Security Plan. Your team represents a small tech firm and you are tasked with making your firm’s proposal to a local _____________________ firm regarding their network policies and procedures. Your proposal will be presented in the form of a PowerPoint presentation (20 slides) The presentation must include: Title Slide with details about the company that you are presenting to on the Notes Pages of the Title slide “About Us” slide about your company (Company name/logo, etc) Our Proposal/Our Goal Results of your imaginary Needs Assessment of the company) Policies & Procedures recommended Give details/specifics: Physical Security: switch to keyless entry and badges Areas to include: Design Asset management Security including policies Risk management Bibliography Slide (list minimum of 2 sources)

 Curtailing virus propagation of a search engine in social networks. Question: What will be the impact of virus propagation wormhole of a search engine in social networks like Facebook and Instagram? Attach is a summary of my proposal containing my research topic and question, the value and justification. Also attached is the guide to this proposal and should be followed strictly, there is also a similar material in pdf format that is attached to also help the writer aside the additional resources he or she will be using for this writing. Please note that only those with Cyber Security and computing expertise are to work on this paper.

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Washington, DC: Author.Bond, C., Woods, K., Humphrey, N., Symes, W., & Green, L. (2013). Practitioner review: The effectiveness of solution focused brief therapy with children and families: A systematic and critical evaluation of the literature from 1990-2010. Journal of Child Psychology & Psychiatry, 54(7), 707-723. doi:10.1111/jcpp.12058Conoley, C., Graham, J., Neu, T., Craig, M., O’Pry, A., Cardin, S., & … Parker, R. (2003). Solution-focused family therapy with three aggressive and oppositional-acting children: An N=1 empirical study. Family Process, 42(3), 361-374. doi:10.1111/j.1545-5300.2003.00361.xde Castro, S., & Guterman, J. (2008). Solution-focused therapy for families coping with suicide. Journal of Marital & Family Therapy, 34(1), 93-106. doi: 10.111/j.1752-0606.2008.00055.x.Nichols, M., & Davis, S. D. (2020). The essentials of family therapy (7th ed.). Boston, MA: Pearson.Chapter 9, “Cognitive-Behavioral Family Therapy” (pp. 132-149)Chapter 12, “Solution-Focused Therapy” (pp. 175-188)Patterson, T. (2014). A cognitive behavioral systems approach to family therapy. Journal of Family Psychotherapy, 25(2), 132-144. doi:10.1080/08975353.2014.910023Perry, A. (2014). Cognitive behavioral therapy with couples and families. Sexual & Relationship Therapy, 29(3), 366-367. doi:10.1080/14681994.2014.909024Ramisch, J., McVicker, M., & Sahin, Z. (2009). Helping low-conflict divorced parents establish appropriate boundaries using a variation of the miracle question: An integration of solution-focused therapy and structural family therapy. Journal of Divorce & Remarriage, 50(7), 481-495. doi:10.1080/10502550902970587Ramisch, J., McVicker, M., & Sahin, Z. (2009). Helping low-conflict divorced parents establish appropriate boundaries using a variation of the miracle question: An integration of solution-focused therapy and structural family therapy. Journal of Divorce & Remarriage, 50(7), 481-495. doi:10.1080/10502550902970587Washington, K. T., Wittenberg-Lyles, E., Parker Oliver, D., Baldwin, P. K., Tappana, J., Wright, J. H., & Demiris, G. (2014). Rethinking family caregiving: Tailoring cognitive–behavioral therapies to the hospice experience. Health & Social Work, 39(4), 244-250. doi:hsw/hlu031Wheeler, K. (Ed.). (2014). Psychotherapy for the advanced practice psychiatric nurse: A how-to guide for evidence-based practice. New York, NY: Springer.Chapter 12, “Family Therapy” (Review pp. 429–468.)

Use the library and other internet resources to research for information about the history of Cryptography. Write a 3 pages research paper answering these questions.If you were setting up an encryption-based network, what key size would you choose and why? Explain your answer with examples. How can we apply that security protocol in real life situations?Provide at least two references to support your initial post.Please note:Apply APA format on your academic writings.provide 3 pages long (not including title and references) as a word document.Include title page, table of content page.Use time new roman or Arial as font type.Use 12 a font size.Use double spaces.Add running head to the upper left corner of your document.Add page numbers to the upper right corner of your document.Add a references page to the end of your document.Do not re-state the questions.Make you own titles and subtitles.Include at least two sources (i.e. two references) and use them within your in-text citation.Do not use Wikipedia as a reference.

Submit a 5 page paper (APA style) detailing the how Blockchain technology can be implemented to reduce ad fraud and cost while meeting consumers’ increasing expectation for excellent customer service?Sources :PDF attached “What Blockchain Could Mean for Marketing” https://hbr.org/2018/05/what-blockchain-could-mean-for-marketing A Clearer Picture http://c2claritymedia.com/wp-content/uploads/accountability-transparency-in-media-today.pdfCompetitive Info: Digital Ad Fraud To Hit $22B By 2020http://www.insideradio.com/free/competitive-info-digital-ad-fraud-to-hit-b-by/article_6d3c6608-a815-11e7-9e40-bbd2e6133207.htmlAre You Ready to Meet Customer Expectations in 2018? http://fieldservicenews.com/ready-meet-customer-expectations-2018/

Research: Data Mining Applications.Background: As noted by Efraim (2020), data mining has become a popular tool in addressing many complex business problems and opportunities. It has proven to be very successful and helpful in many areas such as banking, insurance, and etc. The goal of many of these business data mining applications is to solve a pressing problem or to explore an emerging business opportunity in order to create a sustainable competitive advantage.Reference: Sharda, R., Delen, Dursun, and Turban, E. (2020). Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support. 11th Edition. By PEARSON Education. Inc.SBN-13: 978-0-13-519201-Research Question: Write a research paper that contains the following: Discuss Customer relationship management using data mining applications. Discuss the Travel industry using data mining applications. Compare and contrast data mining vs statistics.Your research paper should be at least 6 pages (1000 words), double-spaced, have at least 5 APA references, and typed in an easy-to-read font in MS Word (other word processors are fine to use but save it in MS Word format). Your cover page should contain the following: Title, Student’s name, University’s name, Course name, Course number, Professor’s name, and Date.