Today, interpreting data is a critical decision-making factor for businesses and organizations. If your job requires you to manage and analyze all kinds of data, turn to "Head First Data Analysis", where you'll quickly learn how to collect and organize data, sort the distractions from the truth, find meaningful patterns, draw conclusions, predict the future, and present your findings to others. Whether you're a product developer researching the market viability of a new product or service, a marketing manager gauging or predicting the effectiveness of a campaign, a salesperson who needs data to support product presentations, or a lone entrepreneur responsible for all of these data-intensive functions and more, the unique approach in "Head First Data Analysis" is by far the most efficient way to learn what you need to know to convert raw data into a vital business tool. You'll learn how to: determine which data sources to use for collecting information; assess data quality and distinguish signal from noise; build basic data models to illuminate patterns, and assimilate new information into the models; cope with ambiguous information; design experiments to test hypotheses and draw conclusions; use segmentation to organize your data within discrete market groups; visualize data distributions to reveal new relationships and persuade others; predict the future with sampling and probability models; clean your data to make it useful; and, communicate the results of your analysis to your audience. Using the latest research in cognitive science and learning theory to craft a multi-sensory learning experience, "Head First Data Analysis" uses a visually rich format designed for the way your brain works, not a text-heavy approach that puts you to sleep.
Michael Milton將自己的大半職業生涯獻給瞭非盈利機構,幫助這些機構解析和處理從贊助人那裏收集來的數據,提高融資能力。Michael Milton擁有新佛羅裏達學院哲學學位及耶魯大學宗教倫理學學位。多年來,他博覽群書,這些書籍雖字字珠璣,卻枯燥乏味; 驀然抬首, 深入淺齣(Head First)係列圖書讓他眼前一亮,他欣然抓住機會,寫齣瞭這本同樣字字珠璣,兼振奮人心的書。
走齣圖書館和書店,人們會看到他在跑步,攝影,以及親手釀製啤酒。
本来想找点深度一点的书,不过当时到了书店后看了两眼发现书的写法很有意思就买下了。 很多人抱怨书的内容不够深入,这点我不反对。不过在我看来,数据分析与其说是理论或技术,倒不如说是一门手艺,仅仅是拿着几个范例数据按照固定的套路算算,看再多的模型,也是...
評分This is my first time reading the book of Orielly’s Head First series. This series is noted for its quite brain-friendly style which based on brain and cognitive science. The authors use many colloquial expressions, funny pics and dialogues in order to mak...
評分head first的名头很大, 相信原本应该不错 翻译的总体来说还可以, 可以看懂 但是翻译过程中存在不少问题, 没有看原版, 从字面上理解的. 比如有一段对话: xx提出了第二个问题 回答中有一句: 这个最后一个问题是一样的(大概是这样, 原话不记得了, 书没在身边) 试想, 你和别人聊天...
評分读起来的感觉是字大行稀,到处都是图片,说起来,这也是headfirst系列的卖点。 这本书,相当容易理解,哗哗哗的,几百页就过去了。如此厚的一本书,最多1,2个小时就能看完。对于之前全都是自己瞎摸瞎撞的搞数据分析的我来说,颇有醍醐灌顶之感。 问题是,真的太浅了,浅到了...
評分本来想找点深度一点的书,不过当时到了书店后看了两眼发现书的写法很有意思就买下了。 很多人抱怨书的内容不够深入,这点我不反对。不过在我看来,数据分析与其说是理论或技术,倒不如说是一门手艺,仅仅是拿着几个范例数据按照固定的套路算算,看再多的模型,也是...
Head First係列跟數據分析、統計相關的書都特麼弱智到一定程度瞭,適閤天朝有前途的初中生看。。
评分快速掌握的訣竅:對話,圖形,重復
评分一個函數是什麼已經忘的差不多的文科生,僅瞭解excel,看懂瞭(除瞭貝葉斯那部分),而且收益匪淺。推薦。
评分歪果仁的書寫的真有意思,就是內容略簡單瞭些~
评分數據分析的要義是進行比較;因果推斷的前提是不同組彆具有可比性
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