Inferential and discreptive analysis of google play store data to find useful insights about the apps on google play store
1.To check if the type of app has any significant impact the ratings the apps recieve
2.To check if the average ratings for free and paid apps are the same
3.To check if average ratings is same for all the categories of the apps
4.To check if the content rating is independent of the application type
The google playstor dataset has 2000 rows and 8 columns and 6 columns are object type and only 2 columns are numerical
1.After data cleaning from the descriptive statistics we can see that there are 18 different categories of apps with 1498 rows(apps) and 8 columns and Gaming category has most of the apps.
2.From Hypothesis 1 its clear that the type of the app doesn’t have any influence on the rating.
3.Hypothesis 2 proved that the number of installs for paid and free apps are not the same.Its good to concentrate on free apps if they need more installs.
The average rating for the categories of apps are different which can be seen from hypothesis 3. If company's aim is to have good ratings then they have to concentrate on the category of app which they are launching.
4.Hypothesis 4 shows that the content rating is independent of application type.