RS Aggarwal Quantitative Aptitude Book PDF
Hello Aspirants, today we are going to share RS Aggarwal Quantitative Aptitude book for all those students who are preparing for any competitive exam. This book is very helpful to crack any exam such as Railway exam- RRB NTPC, Railway Group d, SSC, UPSSSC, State level exam, bank exam like SBI PO, IBPS, RBI, CAT, MAT, Defence exam, Afcat, and other.
This book is design to keep in mind the level of competition, so it cover easy to hard level question which is very important to understand and to crack any exam also.
This book also play a great role in build a concept because without building concept it is not easy to compete in today’s exam because today’s exam level and competition is very high.
This book also cover all those questions which previously asked in various competitive exams, so to prepare with previously asked question is very important to test yourself for competition.
This book almost cover all competitive exams.
Contents of Quantitative aptitude book
H.C.F and L.C.M of numbers
Square roots and cube roots
Problems on numbers
Problems on ages
Surds and Indices
Profits and loss
Ratio and Proportion
Time and work
Pipes and cisterns
Time and distances
Problems on trains
Boats and Stream
Alligation and Mixtures
Volume of Solids
Stock and shares
Permutations and combinations
Lines and angles
RS Aggarwal Quantitative Aptitude book cover almost all the mathematical topic with solved example and practice test. This book is also the best selling book and it is easily available online as well as offline market.Preparation without this book is incomplete, so anyone prepare for any exam please download free pdf and also share with your friends.
To download pdf Please Join ‘Telegram group’
Disclaimer: Sarkari Rush does not own books pdf, neither created nor scanned. We just provide the link already available on internet and in google drive. If any way it violates the law or has any issues then kindly mail us [email protected] to request removal of the link.
Comment for any feedback and query.