About this 專項課程
100% 在線課程

100% 在線課程

立即開始,按照自己的計劃學習。
靈活的計劃

靈活的計劃

設置並保持靈活的截止日期。
初級

初級

完成時間(小時)

完成時間大約為9 個月

建議 6 小時/週
可選語言

英語(English)

字幕:英語(English), 中文(簡體)...

您將獲得的技能

StatisticsStatistical InferenceR ProgrammingQualitative Research
100% 在線課程

100% 在線課程

立即開始,按照自己的計劃學習。
靈活的計劃

靈活的計劃

設置並保持靈活的截止日期。
初級

初級

完成時間(小時)

完成時間大約為9 個月

建議 6 小時/週
可選語言

英語(English)

字幕:英語(English), 中文(簡體)...

How the 專項課程 Works

加入課程

Coursera 專項課程是幫助您掌握一門技能的一系列課程。若要開始學習,請直接註冊專項課程,或預覽專項課程並選擇您要首先開始學習的課程。當您訂閱專項課程的部分課程時,您將自動訂閱整個專項課程。您可以只完成一門課程,您可以隨時暫停學習或結束訂閱。訪問您的學生面板,跟踪您的課程註冊情況和進度。

實踐項目

每個專項課程都包括實踐項目。您需要成功完成這個(些)項目才能完成專項課程並獲得證書。如果專項課程中包括單獨的實踐項目課程,則需要在開始之前完成其他所有課程。

獲得證書

在結束每門課程並完成實踐項目之後,您會獲得一個證書,您可以向您的潛在雇主展示該證書並在您的職業社交網絡中分享。

how it works

此專項課程包含 5 門課程

課程1

Quantitative Methods

4.7
938 個評分
310 個審閱
Discover the principles of solid scientific methods in the behavioral and social sciences. Join us and learn to separate sloppy science from solid research! This course will cover the fundamental principles of science, some history and philosophy of science, research designs, measurement, sampling and ethics. The course is comparable to a university level introductory course on quantitative research methods in the social sciences, but has a strong focus on research integrity. We will use examples from sociology, political sciences, educational sciences, communication sciences and psychology....
課程2

Qualitative Research Methods

4.5
500 個評分
161 個審閱
In this course you will be introduced to the basic ideas behind the qualitative research in social science. You will learn about data collection, description, analysis and interpretation in qualitative research. Qualitative research often involves an iterative process. We will focus on the ingredients required for this process: data collection and analysis. You won't learn how to use qualitative methods by just watching video's, so we put much stress on collecting data through observation and interviewing and on analysing and interpreting the collected data in other assignments. Obviously, the most important concepts in qualitative research will be discussed, just as we will discuss quality criteria, good practices, ethics, writing some methods of analysis, and mixing methods. We hope to take away some prejudice, and enthuse many students for qualitative research....
課程3

Basic Statistics

4.7
1,826 個評分
495 個審閱
Understanding statistics is essential to understand research in the social and behavioral sciences. In this course you will learn the basics of statistics; not just how to calculate them, but also how to evaluate them. This course will also prepare you for the next course in the specialization - the course Inferential Statistics. In the first part of the course we will discuss methods of descriptive statistics. You will learn what cases and variables are and how you can compute measures of central tendency (mean, median and mode) and dispersion (standard deviation and variance). Next, we discuss how to assess relationships between variables, and we introduce the concepts correlation and regression. The second part of the course is concerned with the basics of probability: calculating probabilities, probability distributions and sampling distributions. You need to know about these things in order to understand how inferential statistics work. The third part of the course consists of an introduction to methods of inferential statistics - methods that help us decide whether the patterns we see in our data are strong enough to draw conclusions about the underlying population we are interested in. We will discuss confidence intervals and significance tests. You will not only learn about all these statistical concepts, you will also be trained to calculate and generate these statistics yourself using freely available statistical software....
課程4

Inferential Statistics

4.4
264 個評分
73 個審閱
Inferential statistics are concerned with making inferences based on relations found in the sample, to relations in the population. Inferential statistics help us decide, for example, whether the differences between groups that we see in our data are strong enough to provide support for our hypothesis that group differences exist in general, in the entire population. We will start by considering the basic principles of significance testing: the sampling and test statistic distribution, p-value, significance level, power and type I and type II errors. Then we will consider a large number of statistical tests and techniques that help us make inferences for different types of data and different types of research designs. For each individual statistical test we will consider how it works, for what data and design it is appropriate and how results should be interpreted. You will also learn how to perform these tests using freely available software. For those who are already familiar with statistical testing: We will look at z-tests for 1 and 2 proportions, McNemar's test for dependent proportions, t-tests for 1 mean (paired differences) and 2 means, the Chi-square test for independence, Fisher’s exact test, simple regression (linear and exponential) and multiple regression (linear and logistic), one way and factorial analysis of variance, and non-parametric tests (Wilcoxon, Kruskal-Wallis, sign test, signed-rank test, runs test)....

講師

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Annemarie Zand Scholten

Assistant Professor
Economics and Business
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Gerben Moerman

Dr.
Faculty of Social and Behavioural Sciences
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Matthijs Rooduijn

Dr.
Department of Political Science
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Emiel van Loon

Assistant Professor
Institute for Biodiversity and Ecosystem Dynamics

關於 University of Amsterdam

A modern university with a rich history, the University of Amsterdam (UvA) traces its roots back to 1632, when the Golden Age school Athenaeum Illustre was established to train students in trade and philosophy. Today, with more than 30,000 students, 5,000 staff and 285 study programmes (Bachelor's and Master's), many of which are taught in English, and a budget of more than 600 million euros, it is one of the largest comprehensive universities in Europe. It is a member of the League of European Research Universities and also maintains intensive contact with other leading research universities around the world....

常見問題

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  • 此课程完全在线学习,无需到教室现场上课。您可以通过网络或移动设备随时随地访问课程视频、阅读材料和作业。

  • 此专项课程不提供大学学分,但部分大学可能会选择接受专项课程证书作为学分。查看您的合作院校了解详情。

  • Time to completion can vary based on your schedule, but most learners are able to complete the Specialization in 10 months.

  • Each course in the Specialization is offered on demand, and may be taken at any time.

  • A basic understanding of scientific principles and research methods may be helpful, but is not required. Only very basic math skills are required, you should be able to perform: addition, subtraction, multiplication, calculation of square, square root, exponents and logarithms.

  • We recommend taking the courses in the order presented, as each subsequent course will build on material from previous courses.

  • Coursera courses and certificates don't carry university credit, though some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

  • At the end of this Specialization, you will be performing your own statistical analyses using the programming language R, with no prior knowledge of programming. Learners who complete the Research Methods and Statistics for Social Science Specialization will learn more about scientific rigor and integrity. You’ll have the methods, statistics and research skills required to complete a typical Masters program in the Social Sciences or the Johns Hopkins Data Science Specialization, and also be ready for more advanced courses on big data or multivariate statistics.

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