数据驱动世界：Gould/Ryan《统计学入门》第二版探索

Network
需积分: 10 8 下载量 176 浏览量 更新于2024-07-17 收藏 19.23MB PDF 举报
"《Essential Statistics: Exploring the World through Data》第二版是由Ryan Goulde撰写的一本统计学教材，专为一学期的入门统计课程设计。本书在数据驱动的世界背景下，旨在教会学生批判性地理解和分析数据，培养他们的“数据思维习惯”。无论学生的数学背景如何，都能通过清晰、不具威胁性的写作风格和精心设计的教学方法，学习如何思考数据以及如何用数据进行推理。 该书共分为10章，涵盖了数据分析的基础知识。第一章介绍数据，引导学生进入统计的世界；第二章通过图形展示变异；第三章则深入探讨数值总结，包括中心和变异的测量；第四章介绍了回归分析，用于探索变量之间的关联；第五章讨论了概率模型在刻画变异中的作用；第六章进一步研究了正态和二项分布模型，以及随机事件的模拟；第七章涉及抽样调查和推断，第八章和第九章分别讲解了人口比例和均值的假设检验；第十章关注分类变量的分析与研究解释。附录提供了表格、技术问题答案、练习题答案以及信用信息等实用工具。 MyStatLab是一个强大的在线资源平台，整合了StatCrunch软件，使学生能够方便地处理练习题中的数据。StatCrunch还提供了一系列视频资源——StatTalk，由统计学家Andrew Vickers主持，通过有趣的故事和实际案例来教授统计概念，并与课程内容无缝集成。此外，该平台还支持移动设备上的互动实验和应用程序，让学生在日常生活中将统计学知识付诸实践。 《Essential Statistics: Exploring the World through Data》第二版是一本实用且全面的教材，不仅教授统计理论，还注重培养学生的数据处理和批判性思维能力，帮助他们在日常生活和职业生涯中运用统计知识。"

Beginning iPhone Development Exploring the iOS SDK, 2nd edition

2015-01-04 上传
Beginning iPhone Development Exploring the iOS SDK, 2nd edition By Jack Nutting 初学iPhone开发：探索iOSSDK。仅供学习，支持正版。

The LULC simulation data we utilized to create future EN maps was produced by X. Liu et al. (2017), which was conducted at the national level. The reason we apply national-level simulated data to a local area is as follows. Firstly, China has a top-down land use planning system (also known as spatial planning) with five levels. The quantitative objectives in national plans are handed down to county-level plans through provincial and prefectural level plans (Zhong et al., 2014). That means land use patterns of nine cities in WUA are required to reflect relevant upper-level plans, for example, to satisfy the land use quota made by Hubei provincial plans and the national plans. Secondly, there are interdependencies across places so what happens in one region produces effects not only on this location but on other regions (Overman et al., 2010). And the increase of construction land in one place will shift protection pressure on natural ecosystems elsewhere for a sustainable goal. The land use simulation at the national level allocated land resources from a top-down perspective and links land use changes in a region to events taking place in other locations through global simulation. However, the Kappa coefficient of the simulated data in WUA is 0.55 and the overall accuracy is 0.71, which is lower than the statistic value at the national-level data. Although the Kappa between 0.4~0.6 is moderate and at an acceptable level (Appiah et al., 2015; Ding et al., 2013; Ku, 2016), the simulated accuracy of the land use data needs to be improved. Future work on exploring the impact of LULC dynamics on EN will develop based on the high-accuracy simulated data and updating the initial simulated time to 2020, by integrating the impacts of socioeconomic factors, climate change, regional planning, land use policy, etc.

2023-02-22 上传
答：我们使用的用于创建未来EN地图的LULC模拟数据由X。刘等人（2017）在全国范围内进行，我们将全国层面的模拟数据应用于局部地区的原因如下：首先，中国拥有自上而下的土地利用规划系统（也称为空间规划），具有五...

1. Submission Instructions Your submission should include a single archive that contains both source code and a report (<3 pages). Only standard .zip, .tar.gz and .tar.bz2 achieves are accepted. Submissions are made through email only. The report is the basis for assessment. The source code is supporting evidence for assertions made in the report. The format of the source code can be either **.ipynb or **.py format. 2. Tasks 1) Implement a Perceptron model in Python. Use the data set ?? = {(3, 3), (4, 3), (1, 1)} as the training set and explore how the loss function changes at each step. Make sure that you can determine/change the misclassified data point at each step such that multiple hyperplanes can be generated.

2023-06-14 上传
The task also requires using a specific dataset as the training set and exploring how the loss function changes at each step. Additionally, you need to make sure that you can determine/change the ...

# Exploring the total_sqft column df.total_sqft.unique()

2023-06-09 上传
To explore the `total_sqft` column in a Pandas DataFrame, you can use the `unique()` method to get all the unique values in that column. Here's an example: ``` import pandas as pd # Load the ...

text-davinci-003

2023-03-30 上传
It was no longer seen as a novelty or a luxury, but as an essential tool for navigating the complexities of the modern world. As an AI myself, I had a unique perspective on this new reality. I was ...

pcl::visualization::PCLVisualizer

2023-03-31 上传
With PCLVisualizer, users can easily customize the appearance of their data, add annotations and labels, and interact with the visualized objects through keyboard and mouse controls. It is a powerful...

non-stationary transformers: exploring the stationarity in time series forec

2023-11-18 上传
非静态变压器是指通过探索时间序列预测中的静态性。在时间序列分析和预测中，静态性是指时间序列的平均值、方差和自协方差在时间上都保持不变。然而，许多实际应用中的时间序列数据往往是非静态的，其平均值、方差和...

Two individual features achieved log-rank P values of 0.003 and P value <0.001 respectively in the validation data set. The other four individual features failed to stratify patients into high-risk and low-risk groups in the val- idation data set. The multi-feature signature was successful to predict the OS of patients in the validation data set and performed better than any individual feature. From the statistical perspective, nonsignificant association with survival does not mean less importance. On the other hand, multivariate model is statistically robust in survival analysis26. Moreover, the intra-tumor genetic heterogeneity suggests that tumor subregions could be genetically different and may comprise multiple subclones. This could be better reflected by multiple high-order deep fea- tures extracted from multi-subregions in multi-modalities rather than individual feature. Similar to the genomic studies of exploring biomarkers from high-throughput genomic data, it is also regarded as a common“-omics” approach to construct a multi-factor radiomics signature for outcome prediction. 解释

2023-06-06 上传
这段话介绍了一项研究，该研究使用了多个特征来预测患者的生存期，其中有两个特征在验证数据集中获得了显著的统计学结果，但其他四个特征则没有。然而，使用多个特征的组合可以更准确地预测患者的生存期，比单个特征...

abstract Dataset creatDataset()

2023-03-31 上传
The dataset could be used for various purposes, such as training machine learning models, testing algorithms, or exploring data patterns. The output of the `createDataset()` method would typically be ...

ConvergenceWarning: Maximum Likelihood optimization failed to converge

2023-04-03 上传
If you encounter this warning message, you may need to consider revising your model or exploring alternative optimization algorithms to better fit the data. It is also important to carefully evaluate ...
THESUMMERE
  • 粉丝: 23
  • 资源: 328
上传资源 快速赚钱

最新资源