Gate dimension 3D

Forecasting: Principles and Practice (3rd ed): Chapter 3: Time Series Decomposition Exercises, from Hyndman textbook.

For this assignment, I created an R Markdown document that demonstrates how to use R to analyze a dataset and render the results into a formatted report. I chose the built-in mtcars dataset so the code would run without requiring external files. In my R Markdown file, I: Imported the dataset and displayed the first few rows. Reported the number of rows and columns. Computed basic summary statistics such as mean, median, standard deviation, and interquartile range. Generated a correlation matrix across all numeric variables. Created a scatterplot showing the relationship between car weight and miles per gallon, including a fitted regression line. I selected HTML as the output format because it allows for interactive viewing in the browser, and it is fully supported by RPubs. After knitting my .Rmd file to HTML, I published the report to RPubs and shared the link with my classmates. This exercise showed me how R Markdown can combine code, analysis, and narrative text into a single reproducible document that can be shared easily online.