In this course, learners will be introduced to the field of statistics, including where data come from, study design, data management, and exploring and visualizing data. Learners will identify different types of data, and learn how to visualize, analyze, and interpret summaries for both univariate and multivariate data. Learners will also be introduced to the differences between probability and non-probability sampling from larger populations, the idea of how sample estimates vary, and how inferences can be made about larger populations based on probability sampling.
提供方
課程信息
393,792 次近期查看
學生職業成果
25%
通過此課程獲得實實在在的工作福利
可分享的證書
完成後獲得證書
100% 在線
立即開始，按照自己的計劃學習。
第 1 門課程（共 3 門）
可靈活調整截止日期
根據您的日程表重置截止日期。
初級
High school algebra
完成時間大約為20 小時
英語（English）
字幕：英語（English）, 韓語
您將學到的內容有
Properly identify various data types and understand the different uses for each
Create data visualizations and numerical summaries with Python
Communicate statistical ideas clearly and concisely to a broad audience
Identify appropriate analytic techniques for probability and non-probability samples
您將獲得的技能
StatisticsData AnalysisPython ProgrammingData Visualization (DataViz)
學生職業成果
25%
通過此課程獲得實實在在的工作福利
可分享的證書
完成後獲得證書
100% 在線
立即開始，按照自己的計劃學習。
第 1 門課程（共 3 門）
可靈活調整截止日期
根據您的日程表重置截止日期。
初級
High school algebra
完成時間大約為20 小時
英語（English）
字幕：英語（English）, 韓語
提供方
密歇根大学
The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future.
教學大綱 - 您將從這門課程中學到什麼
完成時間為 5 小時
WEEK 1 - INTRODUCTION TO DATA
In the first week of the course, we will review a course outline and discover the various concepts and objectives to be mastered in the weeks to come. You will get an introduction to the field of statistics and explore a variety of perspectives the field has to offer. We will identify numerous types of data that exist and observe where they can be found in everyday life. You will delve into basic Python functionality, along with an introduction to Jupyter Notebook. All of the course information on grading, prerequisites, and expectations are on the course syllabus and you can find more information on our Course Resources page.
完成時間為 5 小時
11 個視頻 （總計 114 分鐘）, 7 個閱讀材料, 2 個測驗
11 個視頻
Understanding and Visualizing Data Guidelines3分鐘
What is Statistics?9分鐘
Interview: Perspectives on Statistics in Real Life28分鐘
(Cool Stuff in) Data8分鐘
Where Do Data Come From?12分鐘
Variable Types5分鐘
Study Design6分鐘
Introduction to Jupyter Notebooks9分鐘
Data Types in Python12分鐘
Introduction to Libraries and Data Management13分鐘
7 個閱讀材料
Course Syllabus5分鐘
Meet the Course Team!10分鐘
About Our Datasets2分鐘
Help Us Learn More About You!10分鐘
Resource: This is Statistics10分鐘
Let's Play with Data!10分鐘
Data management and manipulation10分鐘
2 個練習
Practice Quiz - Variable Types30分鐘
Assessment: Different Data Types10分鐘
完成時間為 5 小時
WEEK 2 - UNIVARIATE DATA
In the second week of this course, we will be looking at graphical and numerical interpretations for one variable (univariate data). In particular, we will be creating and analyzing histograms, box plots, and numerical summaries of our data in order to give a basis of analysis for quantitative data and bar charts and pie charts for categorical data. A few key interpretations will be made about our numerical summaries such as mean, IQR, and standard deviation. An assessment is included at the end of the week concerning numerical summaries and interpretations of these summaries.
完成時間為 5 小時
8 個視頻 （總計 92 分鐘）, 2 個閱讀材料, 3 個測驗
8 個視頻
Quantitative Data: Histograms12分鐘
Quantitative Data: Numerical Summaries9分鐘
Standard Score (Empirical Rule)7分鐘
Quantitative Data: Boxplots6分鐘
Demo: Interactive Histogram & Boxplot4分鐘
Important Python Libraries21分鐘
Tables, Histograms, Boxplots in Python25分鐘
2 個閱讀材料
What's Going on in This Graph?10分鐘
Modern Infographics10分鐘
3 個練習
Practice Quiz: Summarizing Graphs in Words15分鐘
Assessment: Numerical Summaries10分鐘
Python Assessment: Univariate Analysis10分鐘
完成時間為 5 小時
WEEK 3 - MULTIVARIATE DATA
In the third week of this course on looking at data, we’ll introduce key ideas for examining research questions that require looking at more than one variable. In particular, we will consider both numerically and visually how different variables interact, how summaries can appear deceiving if you don’t properly account for interactions, and differences between quantitative and categorical variables. This week’s assignment will consist of a writing assignment along with reviewing those of your peers.
完成時間為 5 小時
7 個視頻 （總計 56 分鐘）, 3 個閱讀材料, 3 個測驗
7 個視頻
Looking at Associations with Multivariate Quantitative Data7分鐘
Demo: Interactive Scatterplot2分鐘
Introduction to Pizza Assignment2分鐘
Multivariate Data Selection19分鐘
Multivariate Distributions8分鐘
Unit Testing5分鐘
3 個閱讀材料
Pitfall: Simpson's Paradox10分鐘
Modern Ways to Visualize Data10分鐘
Pizza Study Design Assignment Instructions10分鐘
2 個練習
Practice Quiz: Multivariate Data10分鐘
Python Assessment: Multivariate Analysis15分鐘
完成時間為 6 小時
WEEK 4 - POPULATIONS AND SAMPLES
In this week, you’ll spend more time thinking about where data come from. The highest-quality statistical analyses of data will always incorporate information about the process used to generate the data, or features of the data collection design. You’ll be exposed to important concepts related to sampling from larger populations, including probability and non-probability sampling, and how we can make inferences about larger populations based on well-designed samples. You’ll also learn about the concept of a sampling distribution, and how estimation of the variance of that distribution plays a critical role in making statements about populations. Finally, you’ll learn about the importance of reading the documentation for a given data set; a key step in looking at data is also looking at the available documentation for that data set, which describes how the data were generated.
完成時間為 6 小時
15 個視頻 （總計 223 分鐘）, 7 個閱讀材料, 2 個測驗
15 個視頻
Probability Sampling: Part I10分鐘
Probability Sampling: Part II15分鐘
Non-Probability Sampling: Part I10分鐘
Non-Probability Sampling: Part II9分鐘
Sampling Variance & Sampling Distributions: Part I15分鐘
Sampling Variance & Sampling Distributions: Part II7分鐘
Demo: Interactive Sampling Distribution21分鐘
Beyond Means: Sampling Distributions of Other Common Statistics10分鐘
Making Population Inference Based on Only One Sample14分鐘
Inference for Non-Probability Samples17分鐘
Complex Samples23分鐘
Sampling from a Biased Population15分鐘
Randomness and Reproducibility14分鐘
The Empirical Rule of Distribution18分鐘
7 個閱讀材料
Building on Visualization Concepts5分鐘
Potential Pitfalls of Non-Probability Sampling: A Case Study10分鐘
Resource: Seeing Theory10分鐘
Article: Jerzy Neyman on Population Inference10分鐘
Preventing Bad/Biased Samples10分鐘
Optional: Deeper Dive Reference10分鐘
Course Feedback10分鐘
2 個練習
Assessment: Distinguishing Between Probability & Non-Probability Samples10分鐘
Generating Random Data and Samples20分鐘
審閱
來自UNDERSTANDING AND VISUALIZING DATA WITH PYTHON的熱門評論
由 AT 提供2020年5月21日
Excellent course materials, especially the videos, with content that is thoughtfully composed and carefully edited. Very good python training, great instructors, and overall great learning experience.
由 MC 提供2020年4月19日
Excellent high level introduction, would have like the assessment to be more challenging. The additional materials are just amazing for most of them. The notebooks to practice are also excellent.
由 DT 提供2020年5月27日
This course is very good for the people who are not from programming background as everything related to the concepts is very well explained (with programming support) throughout the course
由 MR 提供2020年6月2日
Never have I come across a course half as interactive as this and it was a much needed confidence booster for a beginner like me. I look forward to completing the specialization : )
關於 Statistics with Python 專項課程
This specialization is designed to teach learners beginning and intermediate concepts of statistical analysis using the Python programming language. Learners will learn where data come from, what types of data can be collected, study data design, data management, and how to effectively carry out data exploration and visualization. They will be able to utilize data for estimation and assessing theories, construct confidence intervals, interpret inferential results, and apply more advanced statistical modeling procedures. Finally, they will learn the importance of and be able to connect research questions to the statistical and data analysis methods taught to them.
常見問題
我什么时候能够访问课程视频和作业？
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
- The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
- The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
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如果订阅，您可以获得 7 天免费试听，在此期间，您可以取消课程，无需支付任何罚金。在此之后，我们不会退款，但您可以随时取消订阅。请阅读我们完整的退款政策。
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