2023-10-13
Dataset ‘dt’ is the measures of happiness across the world, along with other factors, in 2019, that help determine the progress of nations. It measures how much each of the factors(GDP per Capita, Family, Life Expectancy, Freedom, Generosity, Trust Government Corruption) affect happiness of people
Statistics in Psychology
by Kirti Raj
Many statistical practices are used in order to calculate the probability of certain events occurring, including in psychology-related fields. Data modeling aids scientists with observing correlations between different variables, including rates of different psychological conditions, emotions, and humans’ well-being, both physical and mental.
To demonstrate, we will use the “World Happiness Report” data set (via Kaggle), specifically from 2019.
Top 10 Countries
First, let’s see the top 10 countries and their scores
We can see that the difference in scores are very minute. Next, let’s examine the relationship between the GDP per capita and Scores of all nations.
GDP vs Score
## NULL
## `geom_smooth()` using formula = 'y ~ x'
From this, we can see that there is no consistent correlation between happiness scores and a country’s GDP. We can see that the countries with the highest scores all have a GDP of just under 1.4.
Countries/Regions with the Lowest Happiness Scores
## Warning in geom_histogram(stat = "identity"): Ignoring unknown parameters: ## `binwidth`, `bins`, and `pad`
Total Score versus Healthy Life Expectancy
We will now see the relationship between life expectancy and the happiness scores.
## `geom_smooth()` using formula = 'y ~ x'
From this, we can see some correlation between happiness scores and life expectancy, although the relationship is not linear.
Chart Using Plotly
In this plot, we will see the relationship between social support people receive versus the score of the respective country/region.
Determinants of Happiness
Let’s look at the averages of the factors.
Chart
