45534 پروژه R

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شرح پروژه

پروژه برنامه نویسی  R رو هم ارسال میکنم خدمت شما،تا نظر کارشناسش رو جویا بشیم،ممنونم  Please follow the Quantitative Analysis Project flowchart I uploaded in DS7006 Moodle site. There are also some suggestion as below for your reference, which you don’t have to follow exactly, nor have to exhaust every suggested step.

Please start with the data exploration, followed by data analysis, then try regression modelling if you like.

Firstly, look at the distribution of dependent variable (Covid death rate), test it’s statistical normality. If not normally distributed, try to nomalise it. There are some R functions available, such as logrithm, Boxcox(), bestNormalize() as well as Min-Max, Z score and so on. You could look at the distribution and test the statistical normality of some dependent variables, if you would run parametric test(s) on them.

Then look at the correlation between the dependent variable and other variables, give up some variables which has almost no correlation with the dependent variable (Covid death rate).

You could test the difference of Covid death rate between 2020 and 2021, or between seasonal quarters if you like.

You could create a new categorical variable based on Covid death rate. The new categorical variable could have two classes of above / below average Covid death rate, or three classes of high / middle / low Covid death rate, or more classes if you like. You could then do Chi-Squares test or ANOVA test with this new categorical variable if you like.

You might try factor analysis with selected independent variables to get fewer key independent variables. Please exclude the dependent variable (Covid death rate) from factor analysis.

You could then try the multiple regression modelling with Covid death as the dependent variable, or multiple logistic regression modelling with that new categorical variable as the dependent variable if you like.  من اطلاعات و فایل های مورد نیاز رو متعاقبا ارسال میکنم خدمت شما 

You will be provided with data giving patterns of COVID-19 deaths by local

authority area in England. You should analyse these data using a range of

social and economic variables of your choice from the NOMIS Data Portal4

or elsewhere on data.gov.uk. You will integrate the data through an SQLite

database and extract data from it for analysis in R (extracted data as CSV

file to be submitted for review). The data set should be assessed for

reliability, explored, hypotheses raised and appropriately tested, regression

models built. The report should provide a clear understanding of:

▪️ which dependent and independent variables you chose to use,

▪️ which techniques you used and in which order,

▪️ why you chose to apply each of these techniques,

▪️ what outcome resulted at each stage of the analysis and what it means.

State clearly your hypotheses/research questions that you develop from the

literature and through the data exploration. Use tables and visualisations as

appropriate to present your analysis. Show the key elements of your SQL

and R scripts, organised in an appendix. Where texts and other background

reading are cited, a list of references should be provided using Harvard style.

Your report should tell the ‘narrative’ of your analysis project and what

variables seem to best explain the COVID-19 deaths such as in a regression

model rather than just being a ‘catalogue’ of things done to data

Quantitative research processes; relationship with qualitative research; mixed mode

approaches.

▪️ Sources of data and official statistics; handling large data sets.

▪️ Data quality (metadata), cleaning and outlier detection; data integration issues.

▪️ Building a database; database query and exporting tables to other software.

▪️ Exploration of univariate, bivariate and multivariate relationships.

▪️ Creating data visualisations: tables, graphs and maps.

▪️ Probability: normal, binomial, Poisson distributions; Bayesian probability.

▪️ Formulating and testing hypotheses: parametric (incl. ANOVA) and non-parametric

techniques.

▪️ Deriving statistical models: factor analysis, clustering, regression, decision trees;

multi-level models.

▪️ Presentation and evaluation of quantitative analyses

 این مطالبی که امروز خدمتتون ارسال کردم مربوط به یه پروژه برنامه نویسی R هست که با توجه به کل اطلاعات و داده هایی که فرستادم و تحلیل هایی که انجام میشه باید یک فایل word چهار هزار لغتی رو ارسال کنم که جزییات این فایل word رو هم ارسال کردم  پروژه ای که امروز خدمتتون ارسال کردم رو برای هفته آینده میتونم دریافت کنم؟

2537

این پروژه شامل 9 فایل مهم است، لطفا قبل از ارسال پیشنهاد حتما نسبت به بررسی این فایل اقدام فرمایید.

مهارت ها و تخصص های مورد نیاز

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