Summary and Future Scope

1. For significance level of 0.05, i.e., p-value is less than 0.05: There is significant relationship between income per capita of a country and Netflix standard subscription price. Hoever a low R2 value of 0.54 indicates that there is no strong correlation between income and Netflix subscription price for a country. Thus, we cannot jump into conclusion that high income countries are likely to pay more for Netflix subscription.
2. For significance level of 0.05, i.e., p-value is less than 0.05: There is not a significant relationship between income per capita of a country and Netflix standard subscription price.
3. More movies and Tv shows are available in developed countries than in developing countries.
4. There is significant difference in standard Netflix subscription price for countries in three different clusters. Countries in second cluster have in average more standard Netflix subscription price.
5. Decision Tree of depth 7 with Income as a root node can distinguish between netflix subscription price as very low, low, high and very high for this dataset.
6. Decision Tree of depth 7 with inflation as root node can distinguish between developed and developing countries for this dataset.
7. There is no specific pattern by which Netflix library size of different countries varies on the basis of population size.

Future Scope

1. Comparison can be made for different time periods 2010-2015 vs 2015-2022, i.e., one can research whether the improvement in income of a country causes Netflix subscription price to increase over time.
2. We can do state/cities level analysis for different countries to see how subscription price varies in different cities of different countries and what variables are causing these variations.