Summary of the Statistical Methods for the Social Sciences by Agresti - 5th edition
- What are statistical methods? – Chapter 1
- Which kinds of samples and variables are possible? – Chapter 2
- Wat are the main measures and graphs of descriptive statistics? - Chapter 3
- What role do probability distributions play in statistical inference? – Chapter 4
- How can you make estimates for statistical inference? – Chapter 5
- How do you perform significance tests? – Chapter 6
- How do you compare two groups in statistics? - Chapter 7
- How do you analyze the association between categorical variables? – Chapter 8
- How do linear regression and correlation work? – Chapter 9
- Which types of multivariate relationships exist? – Chapter 10
- What is multiple regression? – Chapter 11
- What is ANOVA? – Chapter 12
- How does multiple regression with both quantitative and categorical predictors work? – Chapter 13
- How do you make a multiple regression model for extreme or strongly correlating data? – Chapter 14
- What is logistic regression? – Chapter 15
What are statistical methods? – Chapter 1
1.1 What is statistics and how can you learn it?
Statistics is used more and more often to study the behavior of people, not only by the social sciences but also by companies. Everyone can learn how to use statistics, even without much knowledge of mathematics and even with fear of statistics. Most important are logic thinking and perseverance.
To first step to using statistical methods is collecting data. Data are collected observations of characteristics of interest. For instance the opinion of 1000 people on whether marihuana should be allowed. Data can be obtained through questionnaires, experiments, observations or existing databases.
But statistics aren't only numbers obtained from data. A broader definition of statistics entails all methods to obtain and analyze data.
1.2 What is the difference between descriptive and inferential statistics?
Before being able to analyze data, a design is made on how to obtain the data. Next there are two sorts of statistical analyses; descriptive statistics and inferential statistics. Descriptive statistics summarizes the information obtained from a collection of data, so the data is easier to interpret. Inferential statistics makes predictions with the help of data. Which kind of statistics is used, depends on the goal of the research (summarize or predict).
To understand the differences better, a number of basic terms are important. The subjects are the entities that are observed in a research study, most often people but sometimes families, schools, cities etc. The population is the whole of subjects that you want to study (for instance foreign students). The sample is a limited number of selected subjects on which you will collect data (for instance 100 foreign students from several universities). The ultimate goal is to learn about the population, but because it's impossible to research the entire
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