• Post category:StudyBullet-15
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Exploring inflation trend with R, forecasting future inflation based on historical data, and visualising inflation data

What you will learn

Learn basic fundamentals of macroeconomics and inflation, such as getting to know factors that cause inflation and example of inflation in real life

Learn how to forecast future inflation based on historical data using R

Learn how to find correlation between inflation and interest rate, then, visualise the correlation using scatter plot

Learn how to find correlation between inflation and unemployment rate, then, visualise the correlation using scatter plot

Learn how to visualise inflation data for a specific country using scatter plot in R

Learn how to compare inflation between two countries using R

Investigate inflation trend in 2008 economic crisis using R

Learn how to clean data and remove all NA values from dataset using R

Learn how to find countries with highest inflation rate using R

Learn how to download dataset from Kaggle and import it to R Studio Cloud

Description

Welcome to Macroeconomic Analysis: Investigating Inflation Trend with R course. This is a comprehensive data analysis course where you will be guided step by step on how to perform complex data analysis and visualisation on inflation data using R programming language. This course is a perfect combination of macroeconomics and statistics as you will learn all things about inflation from both perspectives. In the introduction session, you will learn basic fundamentals of R programming language, such as getting to know its use cases and features that R has but Python does not have. Then, continue by learning the basic fundamentals of macroeconomics and inflation, using case study examples to understand inflation better as well as getting to know factors that cause inflation. Afterward, you will also learn how to calculate inflation rate and interest rate as well as understanding the relationship between both of them, especially why in most cases raising the interest rate can help to lower the inflation rate. Before starting the project, you will be guided step by step on how to set up all necessary tools, such as installing R programming language and R Studio which is the IDE that will be used in our project. Meanwhile, for the data source, we are going to get our datasets from Kaggle which is one of the largest data science learning platforms that has a lot of datasets that can be downloaded for free. In the project section, you are going to be conducting analysis and visualisation on two different datasets from Kaggle. At the end of the project, you are also going to learn how to deliver data insights and summaries which highlight all your findings during the project. Last but not least, at the end of the course, we will also go over several solutions that can be implemented to lower inflation rate like effective monetary policy, cutting of unnecessary government spending, and fiscal responsibility.

First of all, before getting into the course, we need to ask ourselves these questions. Why should we learn about inflation? Why should we analyze inflation data using the R programming language? Well, let me ask you this question first, have you ever asked yourself, why a cup of coffee that cost two dollars five years ago but now the same product with the same quality costs three dollars? Or maybe why a gaming desk cost you a hundred dollars three years ago but today the same product from the same brand costs you two hundred dollars. Well, those are a few examples of inflation in real life where your cash today is no longer as valuable as it used to be a couple years ago and you might be wondering why? Well inflation reduces a currency’s purchasing power as what we discussed in the previous example where two dollars could buy you a cup of coffee five years ago but today you need three dollars. There are many factors out there that can potentially cause inflation however the most common factor is the oversupply of cash where there is more cash in the circulation than the actual demand. Let me give you an example, let’s say there is an island with population of a thousand people and there are only a hundred coins in the circulation, obviously in this case, the coin is very valuable as they are a thousand people who want to get those coins but there are only a hundred coins available but what if I told you the island’s ministry of treasury decided to create nine hundred more coins, so now there are a thousand coins in the circulation, obviously, now the value of one coin is definitely not as valuable as it used to be. Hence, what we are going to do in this course is to use data to investigate inflation patterns as well as forecast the inflation rate in the future based on the historical data.


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Below are things that you can expect to learn from the course:

  • Learn basic fundamentals of macroeconomics and inflation, such as getting to know factors that cause inflation and example of inflation in real life
  • Learn basic fundamentals of R programming language and getting to know its use cases
  • Learn how to calculate inflation and interest rate
  • Learn how high interest impacts the market from several perspectives, such as cost of borrowing, consumer spending, real estate market and stock market
  • Learn how to find and download datasets from Kaggle
  • Learn how to upload and import data to RStudio Cloud
  • Learn how to clean data and remove all NA values from dataset using R
  • Learn how to find countries with highest inflation rate using R
  • Learn how to visualize inflation data for a specific country using scatter plot in R
  • Investigate inflation trend in 2008 economic crisis using R
  • Learn how to compare inflation between two countries using R
  • Learn how to forecast future inflation using R
  • Learn how to find correlation between inflation and interest rate, then, visualise the correlation using scatter plot
  • Learn how to find correlation between inflation and unemployment rate, then, visualise the correlation using scatter plot
  • Learn several policies that can be implemented to lower inflation rate
English
language

Content

Introduction

Introduction to the Course
Highlight of the Course
Whom This Course is Intended for?

Tools, IDE, and Datasets

Tools, IDE, and Datasets

Introduction to R Programming Language

Introduction to R

Introduction to Macroeconomics & Inflation

Introduction to Macroeconomics & Inflation

Calculating Inflation & Interest Rate

Calculating Inflation Rate
Calculating Interest Rate

How High Interest Rate Impacts the Market?

How High Interest Rate Impacts the Market?

Installing & Setting Up R Studio IDE

Installing R Studio
Setting Up R Studio Cloud

Downloading Inflation Datasets From Kaggle

Downloading Inflation Datasets From Kaggle

Analysing & Visualising Dataset 1 : Global Inflation

Importing Global Inflation Dataset
Quick Overview of Dataset 1
Finding Countries with Highest Inflation Rates
Visualising Inflation Data with Scatter Plot
Investigating Inflation Trend in 2008 Economic Crisis
Comparing Inflation Between Two Countries
Forecasting Future Inflation Based on Historical Data

Analysing & Visualising Dataset 2: Inflation Interest Unemployment Rate Dataset

Importing Inflation Interest Unemployment Rate Dataset
Quick Overview of Dataset 2
Cleaning Data & Removing NA Values
Finding Correlation Between Inflation & Interest Rate
Visualising Correlation Between Inflation & Interest Rate with Scatter Plot
Finding Correlation Between Inflation & Unemployment Rate
Visualising Correlation Between Inflation & Unemployment Rate with Scatter Plot

Solutions to Lower Inflation Rate

Solutions to Lower Inflation Rate

Conclusion & Summary

Conclusion & Summary