SKU: 78791743748

BBK 89-02 Ford Ranger Explorer 66mm Throttle Body BBK Power Plus Series

$182.70 $203.00
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Description

BBK 89-02 Ford Ranger Explorer 66mm Throttle Body BBK Power Plus SeriesBBK Performance throttle bodies are designed as a direct replacement for the restrictive stock factory throttle body. All BBK Power Plus throttle bodies offer OEM drive ability but with up to 30% improved airflow for improved horsepower, torque and throttle response. Every BBK throttle body is CNC Machined from a new high quality 356 aluminum casting and assembled with features like OEM style die stamped throttle linkages, double sealed bearings, and

BBK Performance throttle bodies are designed as a direct replacement for the restrictive stock factory throttle body. All BBK Power Plus throttle bodies offer OEM drive ability but with up to 30% improved airflow for improved horsepower, torque and throttle response. Every BBK throttle body is CNC Machined from a new high quality 356 aluminum casting and assembled with features like OEM style die stamped throttle linkages, double sealed bearings, and o ringed throttle shafts to make every BBK throttle body the best on the market today. All BBK Performance throttle bodies are designed to improve performance and they work with the vehicles factory tune. No tune is required and BBK throttle bodies are available for many late model American muscle cars and trucks. Fits 1990-2000 Ford Ranger / Explorer 4.0L V6 OHC - Does NOT fix SOHC

Installation Instructions
Warranty
Installation Instructions

This Part Fits:

Year Make Model Submodel
1991-2001 Ford Explorer Eddie Bauer
1995 Ford Explorer Expedition
1993-2001 Ford Explorer Limited
2000-2001 Ford Explorer Postal
1991-2000 Ford Explorer Sport
1991-1999 Ford Explorer XL
2000-2001 Ford Explorer XL Fleet
1999-2001 Ford Explorer XLS
1991-2001 Ford Explorer XLT
2001 Ford Explorer Sport Base
2001 Ford Explorer Sport Trac Base
1990-1992 Ford Ranger Custom
2001 Ford Ranger Edge
1990-1992 Ford Ranger S
1990 Ford Ranger S Plus
1993-1998 Ford Ranger Splash
1991-1993,1997 Ford Ranger Sport
1990-1997 Ford Ranger STX
1993-1996,1998-2001 Ford Ranger XL
1995 Ford Ranger XL Sport
1990-2001 Ford Ranger XLT
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SKU: 78791743748

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4.2 ★★★★★
Based on 9 reviews
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Z
Verified Purchase
Zay
Charlottesville, US
★★★★★ 5
Upside down (Great)
Format: Hardcover
Was extremely relatable and a blessing I gifted this book and want it back lol but I will be ordering again
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on October 23, 2024
R
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Rory Derrick
Omaha, US
★★★★★ 5
Good book
Format: Paperback
Still working through it but I have no complaints. I have a shelf of no starch books and have not been disappointed by any. Some, of course, are better than others but this is a good book.
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Reviewed in the United States on December 2, 2021
C
Verified Purchase
Cory P.
Port Orchard, US
★★★★★ 5
Dive into Algorithms is more like eating a Parfait than trying understand algorithms!
Format: Paperback
Seriously though great writing and explanation along with great history lessons. Also highly recommend for anyone working in the data science field.
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Reviewed in the United States on August 3, 2021
F
Verified Purchase
Frank Gonzalez
Los Angeles, US
★★★★★ 3
Ok content, not great explanations (2.5 our of 5 stars)
Format: Paperback
I found the contents of this book to be simply ok: either too simple, or the more complicated algorithms and concepts would not be as carefully explained as they should have been. It is not a terrible book, but it feels as though the author did not go over many drafts/iterations of this work.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on April 7, 2024
I
Ira Laefsky
Chelsea, US
★★★★★ 5
An Excellent Self-Discovery Approach to Learning Algorithms
Format: Paperback
I have an Ivy League Master's Degree in Computer Science although it was accomplished 35 years ago. Of course, I had to complete an ACM-type course in Algorithms and Data Structures on the undergraduate and graduate level and managed to by rote accomplish enough to satisfy these courses. But until seeing this great book I never had the feeling of gaining an understanding of the approach to learning and building algorithms and the extent to which it is an important component of all programs. By a journey of guided self-discovery the author shows, not only the necessity of algorithms and their canonical forms, but a path to understanding the construction of algorithms to accomplish common and not so common practical problems. These range from the simple to understand, e.g. implementing Russian Peasant Multiplication, to advanced and up to date topics like Machine Learning. The highest praise I can give this book is that as a journey of guided self-discovery it produces an understanding in the reader of the process of constructing and understanding these algorithms and their place in all programming.
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Reviewed in the United States on February 7, 2021

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