Wind Power and Ecology? (Nonlinear perturbations on non-standard statistics on large data bases)

ebook

By D. E. Harrison

cover image of Wind Power and Ecology? (Nonlinear perturbations on non-standard statistics on large data bases)

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Brynda Chelsea Willison is young lady in a small liberial arts college. She believes in the movement of 'Save the Earth' even though she still drinks lots of milk. Cows are not earth friendly according to the movement. She is taken back when the class on fossil fuels almost turns into a demonstration for 'Save the Earth.' The teacher takes the entire class out to make signs for the movement's next march. The teacher made his own textbook by coping and pasting from the Internet with all the answers for the tests are in the back of the book.
Her next class is a math class her father says she will need later. The teacher is from England and is Professor Fensby Culpepper. He is the only instructor that did not stumble all over her name. In fact, he pasted right over the spelling. And he is so British.
Judy her roommate feels Brynda's dressing style comes from whatever is on her half of the floor when she gets up.

Brynda studies the fossil classes' textbook and feels it is just a copy and paste with little truth any place in it. She feels, 'I have to fix this; he is hurting the 'Save the Earth' movement.'
She drops the fossil class and with the British math professor's help starts a yearlong study on using wind power for electric power as stated in the fossil fuel textbook.

Over the Christmas holidays at home Brynda asks for her mother's help in updating her entire attire and looks.

Her study is published at the end of the school year in a professional looking booklet titled:
Wind Power and Ecology? (Non-linear perturbations on non-standard statistics on large data bases.)
Brynda presents the finding in her new wardrobe and make over her mother and sister helped her with.

There were two bomb shells at the presentation. Read and see what they were.

Wind Power and Ecology? (Nonlinear perturbations on non-standard statistics on large data bases)