代写Portfolio Project 3代做Python程序

Portfolio Project 3

In this portfolio project, you or your team will have three deliverables, each requiring you to conduct a diferent type of hypothesis test. Below, we’ll refer to "you", but remember, you’re always working in a group!

Deliverable 1: Connecting Hypothesis Testing with Confidence Intervals

In this deliverable, you will collect data on something that you’re interested in. Based on that data, you will then

(i)         construct a confidence interval

(ii)        conduct a two-sided hypothesis test.

Because the choice of parameter is left to you, this means that you will have to be the one to collect data. Our intent is to encourage you to – momentarily – tear your eyes from your screens and go out into the world to gather your evidence!

Your work will be a composition of learning goals 1-4, stated below, and will culminate in a slide deck consisting of 6 total pages. Please reference the format below for your slide deck.

Formatting of Deliverable 1:

Please submit one slide deck; you can create the slide deck in any program, but it should be submitted as a pdf le on GradeScope.

o Learning Goal 1: (30 points) Slides 1-3 of your slide deck.

o Learning Goal 2: (10 points) Slide 4 of your slide deck.

o Learning Goal 3: (15 points) Slide 5 of your slide deck.

o Learning Goal 4: (15 points) Slide 6 of your slide deck.

In what follows, we will state the learning goals for this deliverable.

Learning Goal 1: Defining an objective, gathering evidence, and constructing a point estimate

1. Dening your objective: provide the following on Slide 1

Here, you need to come up with a parameter that you can collect data about in person and hypothesize what it may be for the population. It is important that this is something that you could actually collect data on! This parameter could be a mean or a proportion. Some examples:

Mean:

The average number of students in study rooms of JFF is 3.

The average number of Teslas on the oor of McCarthy Parking Garage is 2.5.

The average height of students on campus is 5’7”.

Proportion:

The fraction of cars that pass USC on Expo which are red is .1.

The fraction of students wearing USC swag on campus is .8.

The fraction of spots empty in the McCarthy parking garage at noon is .05.

a.   (2.5 points) State your parameter of interest

i.   e.g. “I am interested in the average number of students in study rooms in JFF.”

b.   (2.5 points) State your hypothesized value for the parameter

i.   E.g. “I believe the average number of students in study rooms in JFF is 3.”

c.   (2.5 points) State your choice of α ∈ (0,1), which is 1 minus your confidence level.

2. Gathering evidence: provide the following on Slide 2

a.   (10 points) Summarize your data and display a picture of yourself whilst on your data collection adventure

i.   (5 points) provide a seven number summary.

ii.   (2 points) describe in a few sentences how you collected the data.

iii.   (3 points) picture of you collecting your data.

b.   (2.5 points) Report your sample size n

3. Point estimation: provide the following on Slide 3

a.   (5 points) Based on your data, report a point estimate for your parameter

b.   (5 points) Based on your point estimate, report its sampling distribution Learning Goal 2: Constructing a condence interval

1.   Provide the following on Slide 4

a.   (10 points) Based on your results from Learning Goal 1, report your 1 一 α confidence interval for your parameter.

Learning Goal 3: Conducting a two-sided hypothesis test

1.   Provide the following on Slide 5

a.   (5 points) Based on your results from Learning Goal 1, state your null and alternative hypotheses for a two-sided hypothesis test

b.   (10 points) Report your p-value

Learning Goal 4: Putting it all together

1.   Provide the following on Slide 6

a.   (2.5  points) Based on your results from Learning Goal 2, report on whether your hypothesized parameter value falls within your 1 一 α confidence interval

b.   (2.5 points) Based on your results from Learning Goal 3, report on your decision to reject your null hypothesis

c.   (5 points) Answer the following: what is the connection between your responses to questions (a) and (b)? More generally, what is the connection between a confidence interval and a two-sided hypothesis test?

d.   (5 points) Answer the following: what are the pros / cons between (i) reporting the entire confidence interval or p-value versus (ii) simply reporting a “yes” / “no” on whether your  hypothesized value falls within the  interval or a  hard decision on whether you reject your null hypothesis?

Deliverable 2 & 3: Benfords Law

When interviewing for quantitative positions, you'll often meet with professionals who are just a few years ahead of you in their careers and may believe they have a much stronger grasp of math than you do. If you can share something intriguing about mathematics that they’re unfamiliar with, you’ll demonstrate both your knowledge and quantitative expertise.

In deliverable 2 & 3, you will learn about “Benford’s Law”, a seeming paradox / unexpected fact about the distribution of leading numbers in datasets which draw from distributions that span multiple orders of magnitude. (We actually touched on this in class! Can you recall the session?) You will show that Benford’s Law holds in all sorts of surprising datasets. Fortunately, few people know about this interesting law, so it’s a perfect way to surprise an interviewer with how smart you are!

Formatting / Deliverables:

Learning Goal 5: Nothing needs to be submitted.

Learning Goal 6: (60 points available) Submit answers to your questions in the attached worksheet as a .pdf.

Learning Goal 7: (20 points available) Submit a short video of you explaining Benford’s Law, why it is so surprising, and how it can be used to detect fraudulent business records.

Assignment:

Learning goal 5: independently learning about complex statistical subjects.

Learn about Benford’s Law. Here are places where you can learn about it. You’ll know you’ve learned about it when you can say what it is, when it can be applied, and why it’s useful.

1.   Readings:

a. https://en.wikipedia.org/wiki/Benford%27s_law

b. https://www.isaca.org/resources/isaca-journal/past-issues/2011/understanding-and-applying-benfords-law

c. https://www.scientificamerican.com/article/what-is-benfords-law-why-this- unexpected-pattern-of-numbers-is-everywhere/

2.   On YouTube, you can watch some of the following:

a.   (Great video) Numberphile: https://www.youtube.com/watch?v=XXjlR2OK1kM

b.   (About politics) Stand-up Maths:

https://www.youtube.com/watch?v=etx0k1nLn78

c.   (Short and sweet) Minding The Data:

https://www.youtube.com/watch?v=42fGFDNs-0A

3.   If you have Netflix, watch Season 1 Episode 4 “Digits” of the show Connected: The Hidden Science of Everything”. This is a little pop-sciencey, but it’s entertaining.

4.   If you don’t understand Benford’s Law after these resources, it is a good time to practice hunting for information you don’t know. Google Benford’s law and see if people have discussed what you don’t understand.

Due: Nothing needs to be submitted.

Learning Goal 6: Conducting Chi-Square Goodness of Fit tests.

Go to https://testingbenfordslaw.com/ and select 3 of the available datasets that interest you.

Then, run hypothesis tests on each to see if they follow Benford’s Law.

If you need help testing Benford’s Law in Excel, read this article which describes it:

https://www.isaca.org/resources/isaca-journal/past-issues/2010/using-spreadsheets-and- benfords-law-to-test-accounting-data

Due: Fill out the Learning Goal 6 worksheet with the following information.

1.   (10 points each) Go to https://testingbenfordslaw.com/ and select 3 of the available datasets that interest you.

You can switch between datasets using the following drop-down menu in the top right:

2.   For each dataset:

a.   (1 point) Record the number of records.

b.   (1 point) Record the orders of magnitude.

c.   (1 point) Record the frequency of each leading digit.

d.   (2 points) Find the expected count and the actual count of each leading digit.

e.   (5 points) Using a Chi-square goodness of fit test, test whether the observed distribution matched the expected distribution of Benford’s Law at the 5% significance level.

3.   (10 points) In 4-5 sentences, why is it surprising that Benford’s Law held (or nearly held) across your three datasets?

Learning Goal 7: Practice describing Benfords Law to potential recruiters.

The goal if this assignment is to practice explaining Benford's Law in a compelling way, that way you can show it o; to recruiters. You’ll record a 60 second video of you doing just that. If you work in groups, make sure all group members show up and speak out in the video.

Due:

1.   (20 points) Record a video of yourself succinctly explaining Benford's Law. The video should be a minimum of 60 seconds long. You should cover three topics:

a.   What is Benford’s Law

b.   What makes it interesting (using one of your datasets as an example)

c.   Describe how it can be used to detect fraud in business settings.

Get extra practice by recording you telling a friend or family member about Benford’s Law!





热门主题

课程名

mktg2509 csci 2600 38170 lng302 csse3010 phas3226 77938 arch1162 engn4536/engn6536 acx5903 comp151101 phl245 cse12 comp9312 stat3016/6016 phas0038 comp2140 6qqmb312 xjco3011 rest0005 ematm0051 5qqmn219 lubs5062m eee8155 cege0100 eap033 artd1109 mat246 etc3430 ecmm462 mis102 inft6800 ddes9903 comp6521 comp9517 comp3331/9331 comp4337 comp6008 comp9414 bu.231.790.81 man00150m csb352h math1041 eengm4100 isys1002 08 6057cem mktg3504 mthm036 mtrx1701 mth3241 eeee3086 cmp-7038b cmp-7000a ints4010 econ2151 infs5710 fins5516 fin3309 fins5510 gsoe9340 math2007 math2036 soee5010 mark3088 infs3605 elec9714 comp2271 ma214 comp2211 infs3604 600426 sit254 acct3091 bbt405 msin0116 com107/com113 mark5826 sit120 comp9021 eco2101 eeen40700 cs253 ece3114 ecmm447 chns3000 math377 itd102 comp9444 comp(2041|9044) econ0060 econ7230 mgt001371 ecs-323 cs6250 mgdi60012 mdia2012 comm221001 comm5000 ma1008 engl642 econ241 com333 math367 mis201 nbs-7041x meek16104 econ2003 comm1190 mbas902 comp-1027 dpst1091 comp7315 eppd1033 m06 ee3025 msci231 bb113/bbs1063 fc709 comp3425 comp9417 econ42915 cb9101 math1102e chme0017 fc307 mkt60104 5522usst litr1-uc6201.200 ee1102 cosc2803 math39512 omp9727 int2067/int5051 bsb151 mgt253 fc021 babs2202 mis2002s phya21 18-213 cege0012 mdia1002 math38032 mech5125 07 cisc102 mgx3110 cs240 11175 fin3020s eco3420 ictten622 comp9727 cpt111 de114102d mgm320h5s bafi1019 math21112 efim20036 mn-3503 fins5568 110.807 bcpm000028 info6030 bma0092 bcpm0054 math20212 ce335 cs365 cenv6141 ftec5580 math2010 ec3450 comm1170 ecmt1010 csci-ua.0480-003 econ12-200 ib3960 ectb60h3f cs247—assignment tk3163 ics3u ib3j80 comp20008 comp9334 eppd1063 acct2343 cct109 isys1055/3412 math350-real math2014 eec180 stat141b econ2101 msinm014/msing014/msing014b fit2004 comp643 bu1002 cm2030
联系我们
EMail: 99515681@qq.com
QQ: 99515681
留学生作业帮-留学生的知心伴侣!
工作时间:08:00-21:00
python代写
微信客服:codinghelp
站长地图