Products reviews
Celestron Omni XLT 127 (300 x 127mm) Telescope$573.00 to $629.00
Tags:celestron, omni, xlt, 127, 300, x, 127mm, telescope, | Celestron NexStar 5 SE (300 x 44.45mm) Telescope$699.00 to $820.00
Tags:celestron, nexstar, 5, se, 300, x, 44.45mm, telescope, | Educational Insights 5273 (80 x 50mm) Telescope$63.00 to $90.00
Tags:educational, insights, 5273, 80, x, 50mm, telescope, |
Galileo FS-80 Telescope

The Galileo FS-80 reflector telescope is a great beginner's reflecting telescope. The large 80mm primary mirror cell collects 33% more light than a 60mm refracting telescope. 1.25 focus housing permits the use of larger higher quality 1.25 eyepieces. Yoke mount makes the telescope easy to manage through altitude / azimuth (Up & Down, Left & Right) movement, and altitude slow motion control rod for precision adjustmentsMinimize
Celestron PowerSeeker 127 EQ 21049 (750 x 127mm) Telescope

The PowerSeekers come in a choice of refractor or reflector, equatorial or altazimuth mount design. The PowerSeekers come with all coated glass optical components with for enhanced image brightness and clarity. The Newtonian reflectors offer larger aperture and greater light gathering power needed to resolve the faint detail of hundreds of deep-sky and other celestial objects.Minimize
Celestron PowerSeeker 70 EQ 21037 (35 x 70mm) Telescope

Celestron’s PowerSeekers include a full range of eyepieces plus a 3x Barlow lens that provides an increase in viewing power hundreds of times greater than that of the unaided eye!
Meade DS-2080ATS Telescope

Meade Digital Series telescopes bring microprocessor technology and the very latest in electromechanical design to the serious beginning or intermediate observer. Completely re-engineered and redesigned, Meade DS-2080AT telescopes provide extremely smooth motions in both altitude and azimuth, and, most importantly, include a fully integrated Autostar control system as standard equipment. Oversize bearings on both telescope axes of all models negate the imprecisions found universally, virtually without exception, on competing models.Minimize