# Lessons

### Measurement and Measurement levels (demo, no login required)

Carrying out measurements and understanding and using measurement levels.

### Tables and Graphs (login required)

This module discusses how data can be orderly displayed in tables and graphs.

### Measures of Central Tendency (login required)

The measures of central tendency: the mean, the median, and the mode, indicate around which value the scores in a distribution are distributed.

### Measures of Variance (login required)

Measures of variance describe the degree of concentration of observations.

### Skewness (login required)

A skewed distribution is a distribution that is not symmetrical.

### Transformations (login required)

A transformation is a conversion of scores according to a given formula.

### Correlation (login required)

Association between variables or the degree in which high scores on one variable go with high scores on another variable, or low scores on one variable go with low scores on another variable.

### Regression Analysis (login required)

Regression analysis is a method to predict the value of a variable when we know the value of another variable.

### Probability (login required)

Probability is a statistical method with which we assign probabilities to outcomes.

### Random Variables (login required)

Random variables are variables with values which are dependent on the outcome of a random event.

### Probability distributions (login required)

Probability distributions describe the way in which probabilities are distributed among the outcomes of discrete or continuous random variables.

### Sampling distributions (login required)

A sampling distribution is the distribution of a variable as a result of a random selection from the population distribution of the variable.

### Estimation (login required)

An estimate is used to estimate an unknown parameter in the population and it is derived from sample information.

### Hypothesis testing (login required)

Hypothesis testing is a procedure in which a statistical hypothesis about the distribution of the population is rejected or accepted based on the information of a sample.

### t test (login required)

With the t test we can test (1) if a population mean differs from a specific value or (2) if two population means differ from each other, when the variances of the populations are unknown.

### Correlation testing (login required)

Correlation testing is a procedure in which a specific hypothesis about the population correlation is tested.

### The median and proportions (login required)

The sign test and the tests for proportions are used for testing variables measured at ordinal measurement level. The tests do not require a normal distribution.

### Rank-order tests (login required)

The Wilcoxon Signed Ranks Test and the Wilcoxon-Mann-Whitney Test are used to test hypotheses about measures of central tendency.

### The Chi-Square Test (login required)

The Chi-Square Test is used for hypothesis testing of frequency distributions of variables measured at nominal measurement level.

### Dichotomous measures (login required)

The relationship between two dichotomous variables is analysed with measures of association.

### Polytomous variables measured at nominal measurement level (login required)

Using measures of association we can determine the association between two polytomous variables measured at nominal measurement level.

### Polytomous variables measured at ordinal measurement level (login required)

With measures of association we can determine the association between two polytomous variables measured at ordinal measurement level.

### Table Elaboration (login required)

Associations between more than two variables measured at nominal, interval, or ratio measurement level.

### Analysis of Variance (login required)

With the analysis of variance we can determine if two or more means differ from each other.