Data Analysis Workshop
In this workshop, you will perform data analysis tasks using R. You
will learn to create interactive visualizations, calculate statistical
measures, and interpret the results. You will use the dplyr, ggplot2,
and plotly packages to complete the tasks. The goal is to deepen your
understanding of data manipulation, visualization, and statistical
analysis.
Install and load the packages UsingR and MASS.
brightness contain information on the brightness of 963
stars.
- Represent these data employing a histogram and a superimposed
density plot.
- Graphically represent these data using a boxplot. Would you say that
the data have “outliers”? What is the second smallest outlier?
- We want to keep data that cannot be considered outliers. Create a
new variable called brightness.without containing only the values
without outliers.
- Describe the shape of the distribution, any skewness, and the
presence of any modes.
- UScereal contain information on the breakfast with cereals.
- Determine and interpret the relationships between the following
pairs of variables using scatter plots, boxplots, or bar charts as
appropriate:
- manufacturer & shelf.
- fat & vitamins.
- fat & shelf.
- carbohydrates & sugars.
- fibre & manufacturer.
- sodium & sugars.
- Discuss any patterns, trends, or correlations you observe.
- mammals contain information on relationship between body weight and
brain weight of mammals.
- Plot the data to visualize the relationship.
- Is there a linear correlation between these variables?
- Transform the data using the log function and repeat the study. How
do the results change?
- Anorexia contain information on weight change in female
patients.
- What treatment was most effective?
- How many patients gained and how many lost weight?