Critically Analyze Research and Results Using R. Learn to recognize sloppy science, perform solid research and do appropriate data analysis.

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Methods and Statistics in Social Sciences 專項課程

University of Amsterdam

About this 專項課程

Identify interesting questions, analyze data sets, and correctly interpret results to make solid, evidence-based decisions.

This Specialization covers research methods, design and statistical analysis for social science research questions. In the final Capstone Project, you’ll apply the skills you learned by developing your own research question, gathering data, and analyzing and reporting on the results using statistical methods.

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初級

完成時間大約為9 個月

建議 6 小時/週

英語（English）

字幕：英語（English）, 中文（簡體）...

您將獲得的技能

StatisticsStatistical InferenceR ProgrammingQualitative Research

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....

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....

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....

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)....

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....

How long does it take to complete the Research Methods and Statistics in Social Science Specialization?

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

此专项课程中每门课程的开课频率为多久？

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

What background knowledge is necessary?

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.

Do I need to take the courses in a specific order?

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

Will I earn university credit for completing the Research Methods and Statistics Specialization?

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.

What will I be able to do upon completing the Research Methods and Statistics Specialization?

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.