Statistics
This course provides an introduction into descriptive and inferential statistical analysis and hypothesis testing applied to psychological research data.
Specific Contents
- Test theory, hypothesis testing, Type 1 and Type 2 error
- Frequency distribution, mean, mode, median, standard deviation
- Variance, normal distribution, normal distribution with hypothesis testing
- Sampling distribution of means
- Correlation techniques, simple regression
- ANOVA
Learning Goals
The course aims to motivate in students an intrinsic interest in statistical thinking, instill the belief that Statistics is important for scientific research, and provide a foundation and motivation for exposure to statistical ideas subsequent to the course.
Students will be able to
- Demonstrate the ability to apply fundamental concepts in exploratory data analysis.
- Design studies for obtaining data whilst avoiding common design flaws that incur bias, inefficiency and
- Demonstrate an understanding of the basic concepts of probability and random variables.
- Understand the concept of the sampling distribution of a statistic, and in particular describe the behavior of the sample mean.
- Understand the foundations for classical inference involving confidence intervals and hypothesis testing.
- Apply inferential methods relating to the means of Normal distributions.
- Apply and interpret basic summary and modelling techniques for bivariate data and use inferential methods in the context of simple linear models with Normally distributed errors.
- Demonstrate an appreciation of one-way analysis of variance, i. e. ANOVA.
Academic Assessment
Written exam with a duration of 60 minutes.