Experiments aim to determine causal relationships between variables by manipulating one variable and observing its effects. They have advantages like determining causality and direction of influence but disadvantages like artificial conditions and requiring large numbers. True experiments use control and treatment groups, with subjects randomly assigned to determine if a variable A causes an outcome B. More sophisticated designs like the Solomon four-group control for threats to validity by adding multiple pre and post-tests across several groups. Experiments allow isolating the effect of specific variables but rarely mimic real-life conditions.