xuebaunion@vip.163.com

3551 Trousdale Rkwy, University Park, Los Angeles, CA

留学生论文指导和课程辅导

无忧GPA：https://www.essaygpa.com

工作时间：全年无休-早上8点到凌晨3点

扫码添加客服微信

扫描添加客服微信

R代写-STAT 231-Assignment 1

时间：2021-01-20

STAT 231 Online Assignment 1

Assignment 1 is due on Thursday January 21 at 11:00 am EST.

Your assignment submission must be typed. There are no exceptions.

Any submitted answer which is not typed will not be marked but given a mark of

zero.

You may create your document in Word, Google Docs, LaTeX or any other word

processor. The requirement to type your assignment is to facilitate the marking of

hundreds of assignments so that the marked assignments can be returned to you in a

timely fashion. It is also useful for you to gain some experience in creating a

document containing mathematical expressions especially in this time of doing

everything online! Two documents have been posted in the Assignment 1 folder in

LEARN on how to use the equation editor in Word.

Follow the steps in the document Introduction to R and RStudio (posted on the

course website on Learn) to install the software needed for this course. See Section 1

- Introduction. To learn how to run R code see Section 2 – Getting Started.

Upload your assignment to Crowdmark as a pdf file. Here is a useful link for all

information related to Crowdmark assessments: https://crowdmark.com/help/

You can upload your assignment as one document or individually for each problem. If

you upload one document then you must drag and drop the pages for each problem

to the appropriate question as indicated in Crowdmark. You can resubmit your

assignment any number of times before the due time. Therefore to ensure that there

are no issues with uploading we advise you to upload your assignment well in

advance of the due time.

Assignments which are left as a single document and not uploaded to the appropriate

places in Crowdmark will be assigned a 10% penalty.

A penalty of 10% per hour is applied for late assignments.

Please see the course policy on missed assignments on LEARN posted

under Syllabus.

2

In this course we will use many concepts that were covered in STAT 230 (a pre-

requisite for this course). In Problems 1-4 you will review some of these concepts as

well as using the software R to evaluate probabilities. You may find it useful to look

at the review problems 14 to 18 in Chapter 1 of the STAT 231 Course Notes before

attempting this question. A review document about the continuity correction is

posted in the Assignment 1 folder on LEARN.

Problem 1: Binomial distribution

In a very large population 1% of the people have a certain genetic mutation. Suppose 1200 people are

selected at random. Define the random variable Y = number of people with the genetic mutation in

the sample.

(a) What are the assumptions for a Binomial model? Explain, with reasons, whether or not these

assumptions might hold in this context. Your answer must be written in sentences.

(b) Use the Normal approximation to the Binomial with continuity correction and the Normal table in

the Course Notes to approximate the following probabilities.

P(Y ≤ 8), P(Y ≥ 16), and P(|Y – 12| < 7)

You must show your work for full marks.

(c) Type help(pbinom) in R to see the syntax for the R functions pbinom, qbinom, dbinom, and

rbinom. Use the appropriate R functions to obtain values for:

P(Y ≤ 8), P(Y ≥ 16), and P(|Y – 12| < 7)

Include the R statements that you used in your submitted answer.

(d) For each of the probabilities in (b) and (c) determine the percent relative error 100 |−|

where

is the approximate probability and is the probability calculated using R. Explain why each pair of

values is in good agreement or not.

(e) Suppose the proportion of people with the genetic mutation is an unknown value equal to θ.

Suppose n people are selected at random where n is large. Approximate the probability:

�

− 2.17�(1 − )

≤ ≤

+ 2.17�(1 − )

�

You may ignore the continuity correction. You must show your work for full marks.

3

Problem 2: Poisson distribution

During the week of December 6-13, 2020 the visits to an Eastern Ontario Health Unit website to book

a Covid test occurred at random at the average rate of 10 visits per minute. Suppose it is reasonable

to use a Poisson process to model this process. Define the random variable Y = number of visits to the

website in one minute.

(a) Using the three assumptions for a Poisson process argue whether you think it is reasonable or not

for these assumptions to hold in this scenario. Your answer must be written in sentences.

(b) Use the Normal approximation to the Poisson with continuity correction and the Normal table in

the Course Notes to approximate:

P(Y < 5), P(Y > 14), and P(|Y – 10| ≥ 7)

You must show your work for full marks.

(c) Type help(ppois) in R to see the syntax for the R functions ppois, qpois, dpois, and rpois. Use the

appropriate R functions to obtain values for:

P(Y < 5), P(Y > 14), and P(|Y – 10| ≥ 7)

Include the R statements that you used in your submitted answer.

(d) For each of the probabilities in (b) and (c) determine the percent relative error 100 |−|

where

is the approximate probability and is the probability calculated using R. Explain why each pair of

values is in good agreement or not.

(e) Suppose Y1,Y2, …,Yn is a random sample from a Poisson(θ) distribution and let

� = 1

∑

=1 be the sample mean.

Approximate the probability:

�� − 1.61�

≤ ≤ � + 1.61�

�

You may ignore the continuity correction.

You must show your work for full marks.

4

Problem 3: Normal or Gaussian distribution

Suppose it is reasonable to assume that the heights in centimeters of second year female Math

students at the University of Waterloo have a G(160,9) = N(160, 81) distribution. Define the random

variable Y = height of a female Math student chosen at random.

(a) Use the Normal table in the Course Notes to determine P(Y ≥ 169).

You must show your work for full marks.

(b) Type help(pnorm) in R to see the syntax for the R function pnorm, qnorm, dnorm, and rnorm. Use

the appropriate R function to obtain the value for P(Y ≥ 169).

Include the R statement that you used in your submitted answer.

(c) Find the percent relative error 100 |−|

where is the probability determined in (a) using

the Normal table and is the probability determined in (b) using R. Explain why the answers are in

good agreement or not.

(d) Determine a such that P(Y ≥ a) = 0.83 using the inverse Normal cumulative distribution table in the

Course Notes.

You must show your work for full marks.

(e) Use the appropriate R function to obtain the value for a such that P(Y ≥ a) = 0.83.

Include the R statement that you used in your submitted answer.

(f) Are the answers in (d) and (e) in good agreement or not?

(g) Suppose 64 female Math students are chosen at random. Determine the probability that their

average height lies between 159 and 162. Use R to find the probability, not the Normal table in the

Course Notes.

You must show your work for full marks.

Include the R statement that you used in your submitted answer.

5

Problem 4: Exponential distribution

Suppose it is reasonable to model the battery life (in hours) of a certain type of watch battery using

the Exponential(3) distribution. Define the random variable Y = battery life (in hours) of a randomly

chosen watch battery.

(a) With reference to the Memoryless Property of the Exponential Distribution discuss whether you

think an Exponential Model is a reasonable model for Y.

Your answer must be written in sentences.

(b) Determine P(Y ≥ 4) using the probability density function of Y and integration.

You must show your work for full marks.

(c) Type help(pexp) in R to see the syntax for the R functions pexp, qexp, dexp, and rexp. Use the

appropriate R function to obtain the value for P(Y ≥ 4). Include the R statement that you used in your

submitted answer.

(d) Determine the median of this distribution, that is, determine the value m such that

P(Y ≤ m ) = 0.5

You must show your work for full marks.

(e) Suppose Y1,Y2, …,Yn is a random sample from a Exponential(θ) distribution and let

� = 1

∑

=1 be the sample mean.

Approximate the probability:

�� − 1.96

√

≤ ≤ � + 1.96

√

�

You may ignore the continuity correction. Use R to find the probability, not the Normal table in the

Course Notes.

You must show your work for full marks.

Include the R statement that you used in your submitted answer.

6

Problem 5: Empirical Studies

The purpose of this problem is to examine how empirical studies are reported in the

news media.

On the course website on LEARN you will find a module under Additional Resources called Statistics

in the Media. These are all examples of empirical studies which have been reported in the news

media.

Find your own example of statistics in the news media.

Pick a topic which is of interest to you and search online using keywords which describe

your topic.

News media includes print media (newspapers, newsmagazines), broadcast news (radio and

television), and the Internet (online newspapers, news blogs, news videos, live news

streaming, etc.).

Your article must not come from a research journal.

Your example should be less than 2 pages long.

Make sure you chose an example for which the data are a sample of a larger population and

not a census of that population.

The example must have appeared in the news media after December 31, 2019.

(a) Indicate clearly the information on where the article appeared and the date it appeared.

Give the link to the article. To help the TAs mark this question please cut and paste the article into

your assignment.

The answers to (ii) - (vi) must be written in sentences.

(b) Indicate clearly the keywords you used to find your example and why this topic is of interest to

you.

(c) State clearly and succinctly what the purpose of the study was and the conclusion reached by the

researchers.

(d) The study you selected can be best described as which of the following: an observational study, a

sample survey or an experimental study? Justify your answer.

(e) What are the units in this study? Based on the given information, what population or collection of

units are the researchers interested in?

(f) Give the 2 most important variates in this study and indicate the type of each.

7

Problem 6:

The purpose of problem is to use R to generate numerical summaries (see Chapter 1)

and the relative frequency histogram for a Gaussian data set which has been

randomly generated in R. The are two data sets for each sample size of n = 50, 100,

200, and 300. The aim is to compare the observed summaries with what is expected

for Gaussian data.

The R code for this problem is posted as a text file called RCodeAssignment1.txt in

the Assignment 1 folder on LEARN.

Run the R code provided and verify that you obtain the same plots as shown on the

next 4 pages.

Follow the instructions and answer the questions which appear after these plots.

8

9

10

11

12

Run the R code for this problem again except modify the line

"id<-20456484"

by replacing the number 20456484 with your UWaterloo ID number.

When you run the R code with your ID number you will generate 8 new plots. Export

these plots as .png files using RStudio (See Introduction to R and RStudio - Section 6).

(a) My ID number is _________________.

(b) Insert the plots generated using your ID number in your assignment (2 per page).

(c) Each of these data sets was randomly generated from a G(0,1) distribution.

Complete the following sentence and include it with your assignment:

For each data set we expect the sample mean to be close to ______________,

the sample median to be close to _____________, the sample standard deviation to

be close to ______________, the sample skewness to be close to, ______________,

the sample kurtosis to be close to ____________, and the shape of the relative

frequency histogram to be approximately ___________________.

(d) For each of the 8 plots generated using your ID number, compare the observed

numerical summaries and the relative frequency histogram to what is expected for

G(0,1) data. Comment on any differences. What do you notice as the sample size

changes?

Your answer must be written in sentences.

Assignment 1 is due on Thursday January 21 at 11:00 am EST.

Your assignment submission must be typed. There are no exceptions.

Any submitted answer which is not typed will not be marked but given a mark of

zero.

You may create your document in Word, Google Docs, LaTeX or any other word

processor. The requirement to type your assignment is to facilitate the marking of

hundreds of assignments so that the marked assignments can be returned to you in a

timely fashion. It is also useful for you to gain some experience in creating a

document containing mathematical expressions especially in this time of doing

everything online! Two documents have been posted in the Assignment 1 folder in

LEARN on how to use the equation editor in Word.

Follow the steps in the document Introduction to R and RStudio (posted on the

course website on Learn) to install the software needed for this course. See Section 1

- Introduction. To learn how to run R code see Section 2 – Getting Started.

Upload your assignment to Crowdmark as a pdf file. Here is a useful link for all

information related to Crowdmark assessments: https://crowdmark.com/help/

You can upload your assignment as one document or individually for each problem. If

you upload one document then you must drag and drop the pages for each problem

to the appropriate question as indicated in Crowdmark. You can resubmit your

assignment any number of times before the due time. Therefore to ensure that there

are no issues with uploading we advise you to upload your assignment well in

advance of the due time.

Assignments which are left as a single document and not uploaded to the appropriate

places in Crowdmark will be assigned a 10% penalty.

A penalty of 10% per hour is applied for late assignments.

Please see the course policy on missed assignments on LEARN posted

under Syllabus.

2

In this course we will use many concepts that were covered in STAT 230 (a pre-

requisite for this course). In Problems 1-4 you will review some of these concepts as

well as using the software R to evaluate probabilities. You may find it useful to look

at the review problems 14 to 18 in Chapter 1 of the STAT 231 Course Notes before

attempting this question. A review document about the continuity correction is

posted in the Assignment 1 folder on LEARN.

Problem 1: Binomial distribution

In a very large population 1% of the people have a certain genetic mutation. Suppose 1200 people are

selected at random. Define the random variable Y = number of people with the genetic mutation in

the sample.

(a) What are the assumptions for a Binomial model? Explain, with reasons, whether or not these

assumptions might hold in this context. Your answer must be written in sentences.

(b) Use the Normal approximation to the Binomial with continuity correction and the Normal table in

the Course Notes to approximate the following probabilities.

P(Y ≤ 8), P(Y ≥ 16), and P(|Y – 12| < 7)

You must show your work for full marks.

(c) Type help(pbinom) in R to see the syntax for the R functions pbinom, qbinom, dbinom, and

rbinom. Use the appropriate R functions to obtain values for:

P(Y ≤ 8), P(Y ≥ 16), and P(|Y – 12| < 7)

Include the R statements that you used in your submitted answer.

(d) For each of the probabilities in (b) and (c) determine the percent relative error 100 |−|

where

is the approximate probability and is the probability calculated using R. Explain why each pair of

values is in good agreement or not.

(e) Suppose the proportion of people with the genetic mutation is an unknown value equal to θ.

Suppose n people are selected at random where n is large. Approximate the probability:

�

− 2.17�(1 − )

≤ ≤

+ 2.17�(1 − )

�

You may ignore the continuity correction. You must show your work for full marks.

3

Problem 2: Poisson distribution

During the week of December 6-13, 2020 the visits to an Eastern Ontario Health Unit website to book

a Covid test occurred at random at the average rate of 10 visits per minute. Suppose it is reasonable

to use a Poisson process to model this process. Define the random variable Y = number of visits to the

website in one minute.

(a) Using the three assumptions for a Poisson process argue whether you think it is reasonable or not

for these assumptions to hold in this scenario. Your answer must be written in sentences.

(b) Use the Normal approximation to the Poisson with continuity correction and the Normal table in

the Course Notes to approximate:

P(Y < 5), P(Y > 14), and P(|Y – 10| ≥ 7)

You must show your work for full marks.

(c) Type help(ppois) in R to see the syntax for the R functions ppois, qpois, dpois, and rpois. Use the

appropriate R functions to obtain values for:

P(Y < 5), P(Y > 14), and P(|Y – 10| ≥ 7)

Include the R statements that you used in your submitted answer.

(d) For each of the probabilities in (b) and (c) determine the percent relative error 100 |−|

where

is the approximate probability and is the probability calculated using R. Explain why each pair of

values is in good agreement or not.

(e) Suppose Y1,Y2, …,Yn is a random sample from a Poisson(θ) distribution and let

� = 1

∑

=1 be the sample mean.

Approximate the probability:

�� − 1.61�

≤ ≤ � + 1.61�

�

You may ignore the continuity correction.

You must show your work for full marks.

4

Problem 3: Normal or Gaussian distribution

Suppose it is reasonable to assume that the heights in centimeters of second year female Math

students at the University of Waterloo have a G(160,9) = N(160, 81) distribution. Define the random

variable Y = height of a female Math student chosen at random.

(a) Use the Normal table in the Course Notes to determine P(Y ≥ 169).

You must show your work for full marks.

(b) Type help(pnorm) in R to see the syntax for the R function pnorm, qnorm, dnorm, and rnorm. Use

the appropriate R function to obtain the value for P(Y ≥ 169).

Include the R statement that you used in your submitted answer.

(c) Find the percent relative error 100 |−|

where is the probability determined in (a) using

the Normal table and is the probability determined in (b) using R. Explain why the answers are in

good agreement or not.

(d) Determine a such that P(Y ≥ a) = 0.83 using the inverse Normal cumulative distribution table in the

Course Notes.

You must show your work for full marks.

(e) Use the appropriate R function to obtain the value for a such that P(Y ≥ a) = 0.83.

Include the R statement that you used in your submitted answer.

(f) Are the answers in (d) and (e) in good agreement or not?

(g) Suppose 64 female Math students are chosen at random. Determine the probability that their

average height lies between 159 and 162. Use R to find the probability, not the Normal table in the

Course Notes.

You must show your work for full marks.

Include the R statement that you used in your submitted answer.

5

Problem 4: Exponential distribution

Suppose it is reasonable to model the battery life (in hours) of a certain type of watch battery using

the Exponential(3) distribution. Define the random variable Y = battery life (in hours) of a randomly

chosen watch battery.

(a) With reference to the Memoryless Property of the Exponential Distribution discuss whether you

think an Exponential Model is a reasonable model for Y.

Your answer must be written in sentences.

(b) Determine P(Y ≥ 4) using the probability density function of Y and integration.

You must show your work for full marks.

(c) Type help(pexp) in R to see the syntax for the R functions pexp, qexp, dexp, and rexp. Use the

appropriate R function to obtain the value for P(Y ≥ 4). Include the R statement that you used in your

submitted answer.

(d) Determine the median of this distribution, that is, determine the value m such that

P(Y ≤ m ) = 0.5

You must show your work for full marks.

(e) Suppose Y1,Y2, …,Yn is a random sample from a Exponential(θ) distribution and let

� = 1

∑

=1 be the sample mean.

Approximate the probability:

�� − 1.96

√

≤ ≤ � + 1.96

√

�

You may ignore the continuity correction. Use R to find the probability, not the Normal table in the

Course Notes.

You must show your work for full marks.

Include the R statement that you used in your submitted answer.

6

Problem 5: Empirical Studies

The purpose of this problem is to examine how empirical studies are reported in the

news media.

On the course website on LEARN you will find a module under Additional Resources called Statistics

in the Media. These are all examples of empirical studies which have been reported in the news

media.

Find your own example of statistics in the news media.

Pick a topic which is of interest to you and search online using keywords which describe

your topic.

News media includes print media (newspapers, newsmagazines), broadcast news (radio and

television), and the Internet (online newspapers, news blogs, news videos, live news

streaming, etc.).

Your article must not come from a research journal.

Your example should be less than 2 pages long.

Make sure you chose an example for which the data are a sample of a larger population and

not a census of that population.

The example must have appeared in the news media after December 31, 2019.

(a) Indicate clearly the information on where the article appeared and the date it appeared.

Give the link to the article. To help the TAs mark this question please cut and paste the article into

your assignment.

The answers to (ii) - (vi) must be written in sentences.

(b) Indicate clearly the keywords you used to find your example and why this topic is of interest to

you.

(c) State clearly and succinctly what the purpose of the study was and the conclusion reached by the

researchers.

(d) The study you selected can be best described as which of the following: an observational study, a

sample survey or an experimental study? Justify your answer.

(e) What are the units in this study? Based on the given information, what population or collection of

units are the researchers interested in?

(f) Give the 2 most important variates in this study and indicate the type of each.

7

Problem 6:

The purpose of problem is to use R to generate numerical summaries (see Chapter 1)

and the relative frequency histogram for a Gaussian data set which has been

randomly generated in R. The are two data sets for each sample size of n = 50, 100,

200, and 300. The aim is to compare the observed summaries with what is expected

for Gaussian data.

The R code for this problem is posted as a text file called RCodeAssignment1.txt in

the Assignment 1 folder on LEARN.

Run the R code provided and verify that you obtain the same plots as shown on the

next 4 pages.

Follow the instructions and answer the questions which appear after these plots.

8

9

10

11

12

Run the R code for this problem again except modify the line

"id<-20456484"

by replacing the number 20456484 with your UWaterloo ID number.

When you run the R code with your ID number you will generate 8 new plots. Export

these plots as .png files using RStudio (See Introduction to R and RStudio - Section 6).

(a) My ID number is _________________.

(b) Insert the plots generated using your ID number in your assignment (2 per page).

(c) Each of these data sets was randomly generated from a G(0,1) distribution.

Complete the following sentence and include it with your assignment:

For each data set we expect the sample mean to be close to ______________,

the sample median to be close to _____________, the sample standard deviation to

be close to ______________, the sample skewness to be close to, ______________,

the sample kurtosis to be close to ____________, and the shape of the relative

frequency histogram to be approximately ___________________.

(d) For each of the 8 plots generated using your ID number, compare the observed

numerical summaries and the relative frequency histogram to what is expected for

G(0,1) data. Comment on any differences. What do you notice as the sample size

changes?

Your answer must be written in sentences.

- 留学生代写
- Python代写
- Java代写
- c/c++代写
- 数据库代写
- 算法代写
- 机器学习代写
- 数据挖掘代写
- 数据分析代写
- Android代写
- html代写
- 计算机网络代写
- 操作系统代写
- 计算机体系结构代写
- R代写
- 数学代写
- 金融作业代写
- 微观经济学代写
- 会计代写
- 统计代写
- 生物代写
- 物理代写
- 机械代写
- Assignment代写
- sql数据库代写
- analysis代写
- Haskell代写
- Linux代写
- Shell代写
- Diode Ideality Factor代写
- 宏观经济学代写
- 经济代写
- 计量经济代写
- math代写
- 金融统计代写
- 经济统计代写
- 概率论代写
- 代数代写
- 工程作业代写
- Databases代写
- 逻辑代写
- JavaScript代写
- Matlab代写
- Unity代写
- BigDate大数据代写
- 汇编代写
- stat代写
- scala代写
- OpenGL代写
- CS代写
- 程序代写
- 简答代写
- Excel代写
- Logisim代写
- 代码代写
- 手写题代写
- 电子工程代写
- 判断代写
- 论文代写
- stata代写
- witness代写
- statscloud代写
- 证明代写
- 非欧几何代写
- 理论代写
- http代写
- MySQL代写
- PHP代写
- 计算代写
- 考试代写
- 博弈论代写
- 英语代写
- essay代写
- 不限代写
- lingo代写
- 线性代数代写
- 文本处理代写
- 商科代写
- visual studio代写
- 光谱分析代写
- report代写
- GCP代写
- 无代写
- 电力系统代写
- refinitiv eikon代写
- 运筹学代写
- simulink代写
- 单片机代写
- GAMS代写
- 人力资源代写
- 报告代写
- SQLAlchemy代写
- Stufio代写
- sklearn代写
- 计算机架构代写
- 贝叶斯代写
- 以太坊代写
- 计算证明代写
- prolog代写
- 交互设计代写
- mips代写
- css代写
- 云计算代写
- dafny代写
- quiz考试代写
- js代写
- 密码学代写
- ml代写
- 水利工程基础代写
- 经济管理代写
- Rmarkdown代写
- 电路代写
- 质量管理画图代写
- sas代写
- 金融数学代写
- processing代写
- 预测分析代写
- 机械力学代写
- vhdl代写
- solidworks代写
- 不涉及代写
- 计算分析代写
- Netlogo代写
- openbugs代写
- 土木代写
- 国际金融专题代写
- 离散数学代写
- openssl代写
- 化学材料代写
- eview代写
- nlp代写
- Assembly language代写
- gproms代写
- studio代写
- robot analyse代写
- pytorch代写
- 证明题代写
- latex代写
- coq代写
- 市场营销论文代写
- 人力资论文代写
- weka代写
- 英文代写
- Minitab代写
- 航空代写
- webots代写
- Advanced Management Accounting代写
- Lunix代写
- 云基础代写
- 有限状态过程代写
- aws代写
- AI代写
- 图灵机代写
- Sociology代写
- 分析代写
- 经济开发代写
- Data代写
- jupyter代写
- 通信考试代写
- 网络安全代写
- 固体力学代写
- spss代写
- 无编程代写
- react代写
- Ocaml代写
- 期货期权代写
- Scheme代写
- 数学统计代写
- 信息安全代写
- Bloomberg代写
- 残疾与创新设计代写
- 历史代写
- 理论题代写
- cpu代写
- 计量代写
- Xpress-IVE代写
- 微积分代写
- 材料学代写
- 代写
- 会计信息系统代写
- 凸优化代写
- 投资代写
- F#代写
- C#代写
- arm代写
- 伪代码代写
- 白话代写
- IC集成电路代写
- reasoning代写
- agents代写
- 精算代写
- opencl代写
- Perl代写
- 图像处理代写
- 工程电磁场代写
- 时间序列代写
- 数据结构算法代写
- 网络基础代写
- 画图代写
- Marie代写
- ASP代写
- EViews代写
- Interval Temporal Logic代写
- ccgarch代写
- rmgarch代写
- jmp代写
- 选择填空代写
- mathematics代写
- winbugs代写
- maya代写
- Directx代写
- PPT代写
- 可视化代写
- 工程材料代写
- 环境代写
- abaqus代写
- 投资组合代写
- 选择题代写
- openmp.c代写
- cuda.cu代写
- 传感器基础代写
- 区块链比特币代写
- 土壤固结代写
- 电气代写
- 电子设计代写
- 主观题代写
- 金融微积代写
- ajax代写
- Risk theory代写
- tcp代写
- tableau代写
- mylab代写
- research paper代写
- 手写代写
- 管理代写
- paper代写
- 毕设代写
- 衍生品代写
- 学术论文代写
- 计算画图代写
- SPIM汇编代写
- 演讲稿代写
- 金融实证代写
- 环境化学代写
- 通信代写
- 股权市场代写
- 计算机逻辑代写
- Microsoft Visio代写
- 业务流程管理代写
- Spark代写
- USYD代写
- 数值分析代写
- 有限元代写
- 抽代代写
- 不限定代写
- IOS代写
- scikit-learn代写
- ts angular代写
- sml代写
- 管理决策分析代写
- vba代写
- 墨大代写
- erlang代写
- Azure代写
- 粒子物理代写
- 编译器代写
- socket代写
- 商业分析代写
- 财务报表分析代写
- Machine Learning代写
- 国际贸易代写
- code代写
- 流体力学代写
- 辅导代写
- 设计代写
- marketing代写
- web代写
- 计算机代写
- verilog代写
- 心理学代写
- 线性回归代写
- 高级数据分析代写
- clingo代写
- Mplab代写
- coventorware代写
- creo代写
- nosql代写
- 供应链代写
- uml代写
- 数字业务技术代写
- 数字业务管理代写
- 结构分析代写
- tf-idf代写
- 地理代写
- financial modeling代写
- quantlib代写
- 电力电子元件代写
- atenda 2D代写
- 宏观代写
- 媒体代写
- 政治代写
- 化学代写
- 随机过程代写
- self attension算法代写
- arm assembly代写
- wireshark代写
- openCV代写
- Uncertainty Quantificatio代写
- prolong代写
- IPYthon代写
- Digital system design 代写
- julia代写
- Advanced Geotechnical Engineering代写
- 回答问题代写
- junit代写
- solidty代写
- maple代写
- 光电技术代写
- 网页代写
- 网络分析代写
- ENVI代写
- gimp代写
- sfml代写
- 社会学代写
- simulationX solidwork代写
- unity 3D代写
- ansys代写
- react native代写
- Alloy代写
- Applied Matrix代写
- JMP PRO代写
- 微观代写
- 人类健康代写
- 市场代写
- proposal代写
- 软件代写
- 信息检索代写
- 商法代写
- 信号代写
- pycharm代写
- 金融风险管理代写
- 数据可视化代写
- fashion代写
- 加拿大代写
- 经济学代写
- Behavioural Finance代写
- cytoscape代写
- 推荐代写
- 金融经济代写
- optimization代写
- alteryxy代写
- tabluea代写
- sas viya代写
- ads代写
- 实时系统代写
- 药剂学代写
- os代写
- Mathematica代写
- Xcode代写
- Swift代写
- rattle代写
- 人工智能代写
- 流体代写
- 结构力学代写
- Communications代写
- 动物学代写
- 问答代写
- MiKTEX代写
- 图论代写
- 数据科学代写
- 计算机安全代写
- 日本历史代写
- gis代写
- rs代写
- 语言代写
- 电学代写
- flutter代写
- drat代写
- 澳洲代写
- 医药代写
- ox代写
- 营销代写
- pddl代写
- 工程项目代写
- archi代写
- Propositional Logic代写
- 国际财务管理代写
- 高宏代写
- 模型代写
- 润色代写
- 营养学论文代写
- 热力学代写
- Acct代写
- Data Synthesis代写