Title Page
Copyright
Dedication
Epigraph
WHEN AM I GOING TO USE THIS?
PART I
Linearity
One. LESS LIKE SWEDEN
Two. STRAIGHT LOCALLY, CURVED GLOBALLY
Three. EVERYONE IS OBESE
Four. HOW MUCH IS THAT IN DEAD AMERICANS?
Five. MORE PIE THAN PLATE
PART II
Inference
Six. THE BALTIMORE STOCKBROKER AND THE BIBLE CODE
Seven. DEAD FISH DON’T READ MINDS
Eight. REDUCTIO AD UNLIKELY
Nine. THE INTERNATIONAL JOURNAL OF HARUSPICY
Ten. ARE YOU THERE, GOD? IT’S ME, BAYESIAN INFERENCE
PART III
Expectation
Eleven. WHAT TO EXPECT WHEN YOU’RE EXPECTING TO WIN THE LOTTERY
Twelve. MISS MORE PLANES!
Thirteen. WHERE THE TRAIN TRACKS MEET
PART IV
Regression
Fourteen. THE TRIUMPH OF MEDIOCRITY
Fifteen. GALTON’S ELLIPSE
Sixteen. DOES LUNG CANCER MAKE YOU SMOKE CIGARETTES?
PART V
Existence
Seventeen. THERE IS NO SUCH THING AS PUBLIC OPINION
Eighteen. “OUT OF NOTHING I HAVE CREATED A STRANGE NEW UNIVERSE”
HOW TO BE RIGHT
Acknowledgments
Notes
Index
該內容有Taobao 樂讀書屋提供 # http://l-books.taobao.com #
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具體描述
The Freakonomics of math—a math-world superstar unveils the hidden beauty and logic of the world and puts its power in our hands
The math we learn in school can seem like a dull set of rules, laid down by the ancients and not to be questioned. In How Not to Be Wrong, Jordan Ellenberg shows us how terribly limiting this view is: Math isn’t confined to abstract incidents that never occur in real life, but rather touches everything we do—the whole world is shot through with it.
Math allows us to see the hidden structures underneath the messy and chaotic surface of our world. It’s a science of not being wrong, hammered out by centuries of hard work and argument. Armed with the tools of mathematics, we can see through to the true meaning of information we take for granted: How early should you get to the airport? What does “public opinion” really represent? Why do tall parents have shorter children? Who really won Florida in 2000? And how likely are you, really, to develop cancer?
用戶評價
##statistical inference科普
評分##看看
評分##statistical inference科普
評分##讀瞭一半不想讀瞭
評分##作為消遣類的數學科普讀讀，還是很不錯的。雖然有些章節確實有點囉嗦，但是偶爾點綴的小幽默也算是可以消解掉那些囉嗦瞭。
評分##作者把數學根據simple-complicated VS shallow-profound分成四部分，旨在講述profound and simple的部分，燃鵝私以為失敗瞭。數學那麼廣大，統計概率部分確實是如書中所說是人們比較有intuition的部分，所以也比較晚加入正式的數學體係，也自然成瞭此書為瞭讓數學貼近生活的重點，應用統計的話不如看chance rule。感覺這本四不像。不過能感到作者對數學的滿腔熱忱，想感染大眾，心領瞭????
評分##看看
評分##cant even finish it... too general and too common sense
評分##雖然我對書中提到的大部分概念並不陌生，但仍然學到不少東西。作者把很多看似毫不相乾的概念或現象巧妙地聯係到一起，展現齣數學的美妙和無所不在。
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