R Studio Project
Budget: €8 – €30 EUR
Part 1:
Using the techniques of descriptive statistics, perform a detailed exploratory analysis of the
dataset of your choice. Data attached.
Your dataset must be different from the datasets which are used in lectures or lab tutorials.
Your dataset should contain at least 200 observations (rows) and 10 variables (columns).
You are required to submit the code for your analysis. In addition to the code, you are
required to provide a detailed report, clearly identifying the methods you used in the code
for exploratory data analysis. And to report the outcomes of your analysis. You should also
use visual charts and graphs (e.g., histograms, box plots, scatter plots) to provide your
understanding of the dataset.
Your report must address the following sections. 10 marks are dedicated to the working
code submitted. The rest of the Total marks of Part 1 (50) are equally distributed among
these sections.
• a detailed description of which descriptive statistics techniques performed on the
dataset and why
Pre-processing techniques (cleaning, merging, deleting, imputation) applied on the
raw data. Provide your reasoning if you have not applied any pre-processing on the
data
• key insights you gathered from your above analysis about various independent
variables
• Key insights you gathered from your analysis about relationship between
independent & dependent variables
The final report should not include the code and be clearly sectioned, correctly referenced
and not exceed 1000 words. Code must be uploaded using the dedicated link.
Part 2:
Using the dataset of your choice, perform a hypothesis testing using one way and two-way
ANOVA techniques using RStudio. Your test hypothesis should estimate change in mean of
quantitative variable according to the categorical independent variables. You are allowed to
use the same dataset as Part 1 or select a completely new dataset of your choice. Your
dataset should not be greater than 100 rows and 4 columns.
You are required to provide a working code in RStudio. Clearly document the code.
In addition, you are required to provide a report of your finding and an evaluation of the
performance of your model.
Your report must address the following sections. Total marks of Part 2 are equally
distributed among these sections:
• Selection of dataset for ANOVA test
• Clear and thorough hypothesis building
• Clear selection of test parameters
• One-way & two-way ANOVA test
• Evaluation of performance of your model
Document in report format all models generated and provide an evaluation of the models.
The final report should not include the code and be clearly sectioned, correctly referenced
and not exceed 1000 words.
Using the techniques of descriptive statistics, perform a detailed exploratory analysis of the
dataset of your choice. Data attached.
Your dataset must be different from the datasets which are used in lectures or lab tutorials.
Your dataset should contain at least 200 observations (rows) and 10 variables (columns).
You are required to submit the code for your analysis. In addition to the code, you are
required to provide a detailed report, clearly identifying the methods you used in the code
for exploratory data analysis. And to report the outcomes of your analysis. You should also
use visual charts and graphs (e.g., histograms, box plots, scatter plots) to provide your
understanding of the dataset.
Your report must address the following sections. 10 marks are dedicated to the working
code submitted. The rest of the Total marks of Part 1 (50) are equally distributed among
these sections.
• a detailed description of which descriptive statistics techniques performed on the
dataset and why
Pre-processing techniques (cleaning, merging, deleting, imputation) applied on the
raw data. Provide your reasoning if you have not applied any pre-processing on the
data
• key insights you gathered from your above analysis about various independent
variables
• Key insights you gathered from your analysis about relationship between
independent & dependent variables
The final report should not include the code and be clearly sectioned, correctly referenced
and not exceed 1000 words. Code must be uploaded using the dedicated link.
Part 2:
Using the dataset of your choice, perform a hypothesis testing using one way and two-way
ANOVA techniques using RStudio. Your test hypothesis should estimate change in mean of
quantitative variable according to the categorical independent variables. You are allowed to
use the same dataset as Part 1 or select a completely new dataset of your choice. Your
dataset should not be greater than 100 rows and 4 columns.
You are required to provide a working code in RStudio. Clearly document the code.
In addition, you are required to provide a report of your finding and an evaluation of the
performance of your model.
Your report must address the following sections. Total marks of Part 2 are equally
distributed among these sections:
• Selection of dataset for ANOVA test
• Clear and thorough hypothesis building
• Clear selection of test parameters
• One-way & two-way ANOVA test
• Evaluation of performance of your model
Document in report format all models generated and provide an evaluation of the models.
The final report should not include the code and be clearly sectioned, correctly referenced
and not exceed 1000 words.