پروژه R یا پایتون . Data Analysis..

---

شرح پروژه

انجام پروژه بالا با R یا پایتون

کارشناسی ارشد اقتصاد

درس تحلیل داده هستش

Data Analysis

برایم مهم هستش که پروژه فقط از تکنیک های آماری فوق استفاده کنه (و نه چیز پیچیده تر و یا ورای این فایل ها) و این که توضیح راجع به سورس کد و نحوه پژوهش هم ارایه داده بشه.
برای پروژه نیاز هستش که منابع آماری (آمار مرتبط با توزیع درآمد، سطح درآمد و غیره) هم در اختیار کارشناستون قرار بدم (اگر که ایشون این کار رو انجام نمی دن خودشون) که این کار رو هرموقع بهم فرصت تماس و توضیح بدین انجام میدم.

--------------

Methodology

This study investigates the impact of minimum wage legislation on the income distribution in Germany, using robust statistical methods to ensure reliable inference in the presence of skewed data and potential outliers. The methodology combines descriptive analysis, robust estimation techniques, effect size computation, and subgroup analysis to explore distributional shifts across time and population segments.

Data

The primary data source will be the German Socio-Economic Panel (SOEP), a longitudinal microdata set collected annually. Data from the years 2013 to 2017 will be used to construct a pre- and post-policy comparison around the introduction of the statutory minimum wage in 2015. Key variables include:

Gross and net monthly income

Employment type and hours worked

Demographic characteristics (age, gender, education)

Region (East vs. West Germany)

Observations will be limited to working-age individuals (18–65), and part-time or marginally employed workers will be flagged for subgroup analysis.

Data Cleaning and Preparation

Missing values will be identified using the is.na() and summary() functions. Observations with missing income will be inspected for non-random patterns. Where appropriate, multiple imputation using chained equations (MICE) will be applied following guidelines in
.

Income variables will be examined for skewness and heteroskedasticity. As income distributions are typically right-skewed, Box-Cox and Yeo-Johnson transformations will be evaluated to stabilize variance and normalize the data
.

Descriptive Statistics

The analysis will begin with exploratory data visualizations:

Histogram and kernel density estimates to compare income distributions before and after the policy change
.

Boxplots and violin plots to identify outliers and spread.

Descriptive measures such as mean, median, interquartile range, skewness, kurtosis, and Gini coefficient will be reported
.

Robust Estimation

Given the sensitivity of means and standard deviations to extreme values, robust location and scale estimators will be applied:

Huber’s M-estimator

Tukey’s biweight

Median Absolute Deviation (MAD)

These will be computed using the robustbase package in R, following recommendations from
. These estimators will be compared to their classical (non-robust) counterparts.

Inferential Analysis and Effect Sizes

To test for significant changes in income levels and inequality:

Two-sample location tests will be applied (t-tests and Wilcoxon tests), with bootstrapped confidence intervals where appropriate
.

Effect sizes will be computed using Cohen’s d, η², and Cliff’s delta to quantify the magnitude of change, independent of sample size
.

Subgroup Analysis

The effects of minimum wage policies will be analyzed across key subpopulations:

Geographic: East vs. West Germany

Sectoral: Hospitality, retail, and care sectors

Demographic: Gender, education level

Subgroup comparisons will employ ANOVA, Kruskal-Wallis, and post-hoc tests (Tukey HSD or Bonferroni-corrected Wilcoxon) depending on distributional assumptions
.

Robustness Checks

Finally, robustness will be assessed by:

Excluding the top and bottom 1% of income earners

Comparing results from untransformed and transformed data

Repeating key estimates with and without imputed values

These checks will help verify that findings are not driven by a small set of extreme observations or modeling assumptions. 

این پروژه شامل 12 فایل مهم است، لطفا قبل از ارسال پیشنهاد حتما نسبت به بررسی این فایل اقدام فرمایید.

مهارت ها و تخصص های مورد نیاز

---

---