After the course, the student should be familiar with the basic concepts of statistics, ranging from descriptive statistics to basic inference (confidence intervals and hypothesis testing) and linear models (linear a logistic regression).

Knowledge about statistical methods and data analysis is of great importance in almost any field of research. In this course, general concepts of statistics will be provided so that the students can be able to independently carry out a small scale empirical research with the statistical software R.

Contents

1. Basic concepts (1 lecture)
   1. What is statistics?
   2. Statistical research and its phases of work
   3. Population and sample
   4. Types of variables and scales of measurement
2. Descriptive statistics (2 lectures)
   1. What is data?
   2. summary statistics (mean, median, quartiles, standard deviation and variance)
   3. Plotting the data (scatter plot, histogram, QQ-plot and boxplot)
   4. Contingency tables
3. Basics of statistical inference (4-5 lectures)
   1. Basic concepts of probability
   2. Probability distributions (Binomial and Normal)
   3. Basic concepts in sampling theory
   4. Confidence intervals (mean and difference of means in independent samples)
   5. Hypothesis testing (mean and equality of means in independent samples, type I and type II-errors and p-values)
   6. Introduction to some non-parametric tests
4. Linear models (3 lectures)
   1. Introduction to linear regression
   2. Basics of logistic regression
   3. Basics of Analysis of Variance (ANOVA)

A maximum number of 50 students will be allowed in this course (70% doctoral students and 30% masters students).

The evaluation will be based on 4-5 weekly assignments plus a final assignment (ideally analyzing own data).

Please note that this course cannot be included inside the minimum 120 ECTS of Master's Degree Programme in CBDA (basic level course).

MTTTP1 Tilastotieteen johdantokurssi lectured in period I, II or III-IV is recommended for Finnish students.