Growing up in a family of storytellers, Janis Thomas Cramer spent Sunday dinners with the Thomas clan in Muskogee, Oklahoma, where she heard family lore begging to be retold--stories of the Depression, of six sons fighting in World War II, and of a tornado's destroying three family homes. She lived fantastic stories of her own as well, with two brothers and an army of cousins and friends from Riverside School. In the early Sixties, she endured teenage angst with other Baby Boomers crowding into Alice Robertson Junior High School during the New Math, the Race for Space, and the President's Physical Fitness Challenge. “Growing Up Thomas” carries the reader with Janis through some captivating vignettes of her young life.“Come along with Sweetiepie in the Rocket 88. Meet some real Okie characters from the last century. Scratch your head. Laugh out loud. Shed a tear. Be a kid again.” ~~Bill Lehmann, author of "An Okie from Muskogee Recalls Growing up in the Dirty 30s.
Janis Cramer, a true "Okie from Muskogee" Oklahoma, another one in a family of storytellers, has finally compiled experiences of her lifetime into one book, "My Finest." Inside you will find "Grandma's Panties," "My Ten Minutes with Bob Dylan," "2001, a Gorilla Odyssey," and "Some Girls Would," to name a few.Cramer, a creative writing teacher for 18 years at Muskogee High School and 23 years at Mustang High School in Oklahoma, has included in this portfolio of memoirs several genres of writing: childhood experiences, family stories, teacher lore, travel pieces, a professional piece for other teachers, and a couple of poems.Depending on what phase of her life you might have known the author--whether she was Sweetiepie, Janis Thomas, Mrs. Lowrance, or Mrs. Cramer--you might have heard her tell a few of these stories. Now you will have a chance to read the rest.At the end of each chapter is a reflection on the piece, put there for her students to show she practices what she preached. She hopes each piece in this showcase portfolio of her years of work will bring a belly laugh or a tear or two from the reader.
While advice abounds from a variety of sources before parents embark on their parenting journeys, the only parent preparation we actually receive comes from our family and peer stories. Yet most adults do not realize that in day-to-day challenges of guiding our children, something interesting happens. As we steer our children through life, we reopen our own childhood roads. Just when our child most needs us, we become needy ourselves: as adults and parents, we find that we have unresolved raising issues, basic needs that were not met in our childhoods. Our needs and memories echo and influence many of the parenting decisions we make, even though we’re unaware of those influences at times. Fortunately, children help parents reach their needs as much as their parents help them fulfill their own. Our child ends up guiding us, by connecting us to some earlier time in our life when we encountered distress. We dredge up a lesson, and we adapt by adhering to or changing the story that we tell ourselves about who we are. We re-negotiate the five basic needs that surface from our childhood memories as our youngsters pass through each of the developmental phases. The self-aware parent focuses on creative problem solving by focusing on one interaction at a time. It Takes a Child to Raise a Parent offers an exploration of how our own childhood memories and needs influence and shape our parenting decisions in our adult lives. Offering tips, stories from a variety of families, and step by step exercises, Janis Johnston helps parents better understand and grasp the tools necessary to face parenting challenges head on, and to explore new ways of understanding ourselves, our children, and our family interactions. Expectant parents and current parents interested in understanding their own personality development as well as the many moods of childhood and their own children, will find clear guidelines for understanding their roles in their children’s lives as well as concrete suggestions for how to navigate the choppy waters of raising children.
This research monograph utilizes exact and Monte Carlo permutation statistical methods to generate probability values and measures of effect size for a variety of measures of association. Association is broadly defined to include measures of correlation for two interval-level variables, measures of association for two nominal-level variables or two ordinal-level variables, and measures of agreement for two nominal-level or two ordinal-level variables. Additionally, measures of association for mixtures of the three levels of measurement are considered: nominal-ordinal, nominal-interval, and ordinal-interval measures. Numerous comparisons of permutation and classical statistical methods are presented. Unlike classical statistical methods, permutation statistical methods do not rely on theoretical distributions, avoid the usual assumptions of normality and homogeneity of variance, and depend only on the data at hand. This book takes a unique approach to explaining statistics by integrating a large variety of statistical methods, and establishing the rigor of a topic that to many may seem to be a nascent field. This topic is relatively new in that it took modern computing power to make permutation methods available to those working in mainstream research. Written for a statistically informed audience, it is particularly useful for teachers of statistics, practicing statisticians, applied statisticians, and quantitative graduate students in fields such as psychology, medical research, epidemiology, public health, and biology. It can also serve as a textbook in graduate courses in subjects like statistics, psychology, and biology.
This research monograph provides a synthesis of a number of statistical tests and measures, which, at first consideration, appear disjoint and unrelated. Numerous comparisons of permutation and classical statistical methods are presented, and the two methods are compared via probability values and, where appropriate, measures of effect size. Permutation statistical methods, compared to classical statistical methods, do not rely on theoretical distributions, avoid the usual assumptions of normality and homogeneity of variance, and depend only on the data at hand. This text takes a unique approach to explaining statistics by integrating a large variety of statistical methods, and establishing the rigor of a topic that to many may seem to be a nascent field in statistics. This topic is new in that it took modern computing power to make permutation methods available to people working in the mainstream of research. lly-informed="" audience,="" and="" can="" also="" easily="" serve="" as="" textbook="" in="" graduate="" course="" departments="" such="" statistics,="" psychology,="" or="" biology.="" particular,="" the="" audience="" for="" book="" is="" teachers="" of="" practicing="" statisticians,="" applied="" quantitative="" students="" fields="" medical="" research,="" epidemiology,="" public="" health,="" biology.
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