Bred in Scotland, Clydesdales are some of the largest and most powerful horses in the world. They're often seen working in teams to pull wagons and plows. These animals are also called "gentle giants." Readers will learn much about this breed and see the characteristics that make Clydesdales stand out among horses in the full-color photographs this book provides. Easy-to-follow text makes learning about the many jobs of a Clydesdale, from pulling competitions to TV commercials, assessable to the most reluctant of readers.
As people live longer and better lives, both women and men may look forward to many years in retirement. But living well in retirement depends on a variety of decisions people make as they prepare for and enter this new chapter of life and living. This book is for and about women approaching and experiencing life in their senior years. This largest and fastest-growing part of the population is living in a manner very different from our mothers, whose roles in life were much more predictable and circumscribed than ours. Today’s senior women live longer, are healthier, better educated, more involved in the world, and more active than the women who preceded us. Figuring out these uncharted years without role models or guideposts can be challenging, but, here, the authors gather the stories of today’s senior women, who have jumped hurdles, answered questions, and made decisions they never saw their mothers make. Through these stories, readers will find fellowship and guidance, wisdom and acknowledgment of the challenges (and triumphs) that lie ahead. Culled from women in their sixties and beyond, and from a variety of backgrounds and current living situations, the stories reveal the realities of life for retirement-age women, and demonstrate the dreams, joys, concerns, and fears that come along with this phase of life. They address questions about living arrangements, adult children, loss of a spouse or partner, relationships and friendships, part time work, social connections, health concerns, and more. Facing these new situations with class, dignity, sass, and smarts, these women reveal the various ways today’s senior women can live and love her retirement years.
Mama, Do You Love Me?, a tender and reassuring book that both parents and children have turned to again and again, now available in paperback. In this classic, bestselling story of a child testing the limits of her independence, a mother reassures that a parent's love is unconditional and everlasting. This universal story is made all the more captivating by its unusual Arctic setting. Complemented by a detailed glossary, this tender story introduces young readers to a distinctively different culture and shows that the special love between parent and child transcends all boundaries of time and place.
The bestselling and much-loved Mama, Do You Love Me? and its tender companion, Papa, Do You Love Me? are paired in this boxed set of board books, perfect for a new generation of families. Accompanied by beautiful watercolor illustrations and reassuring texts, these heartwarming stories share a universal message: that a parent's love is everlasting and unconditional.
From the bestselling author of Mama, Do You Love Me?— and finally available in a board book format—this classic read-aloud provides a poetic and comforting answer to a universal question: Who do you love more? In this warm celebration of unconditional love, a wise mother reassures her children that each of them has a very special place in her heart, making this a perfect gift for the whole family.
A Primer of LISREL represents the first complete guide to the use of LISREL computer programming in analyses of covariance structures. Rather than writing for the expert statistician, Dr. Byrne draws examples from her own research in providing a practical guide to applications of LISREL modeling for the unsophisticated user. This book surpasses the other theoretically cumbersome manuals, as the author describes procedures and examples establishing for the user the first book requiring no supplement to the understanding of causal modeling and LISREL.
