After psychologists develop a theory, form a hypothesis, make observations,
and collect data, they end up with a lot of information, usually in the form of
numerical data. The term **statistics** refers to the analysis and
interpretation of this numerical data. Psychologists use statistics to organize,
summarize, and interpret the information they collect.

To organize and summarize their data, researchers need numbers to
describe what happened. These numbers are called **descriptive
statistics**. Researchers may use **histograms** or **bar graphs** to show the way data are distributed. Presenting
data this way makes it easy to compare results, see trends in data, and
evaluate results quickly.

Example:Suppose a researcher wants to find out how many hours students study for three different courses. Each course has 100 students. The researcher does a survey of ten students in each of the courses. On the survey, he asks the students to write down the number of hours per week they spend studying for that course. The data look like this:

Course A | Course B | Course C |
|||

Student | Hours per week | Student | Hours per week | Student | Hours per week |

Joe | 9 | Hannah | 5 | Meena | 6 |

Peter | 7 | Ben | 6 | Sonia | 6 |

Zoey | 8 | Iggy | 6 | Kim | 7 |

Ana | 8 | Louis | 6 | Mike | 5 |

Jose | 7 | Keesha | 7 | Jamie | 6 |

Lee | 9 | Lisa | 6 | Ilana | 6 |

Joshua | 8 | Mark | 5 | Lars | 5 |

Ravi | 9 | Ahmed | 5 | Nick | 20 |

Kristen | 8 | Jenny | 6 | Liz | 5 |

Loren | 1 | Erin | 6 | Kevin | 6 |

To get a better sense of what these data mean, the researcher can plot them on a bar graph. Histograms or bar graphs for the three courses might look like this:

Researchers summarize their data by calculating **measures of
central tendency**, such as the mean, the median, and the mode. The
most commonly used measure of central tendency is the **mean**,
which is the arithmetic average of the scores. The mean is calculated by
adding up all the scores and dividing the sum by the number of scores.

However, the mean is not a good summary method to use when the data
include a few extremely high or extremely low scores. A distribution with a
few very high scores is called a **positively skewed distribution**. A distribution with a few very low scores is called a **negatively skewed distribution**. The mean of a positively
skewed distribution will be deceptively high, and the mean of a negatively
skewed distribution will be deceptively low. When working with a skewed
distribution, the median is a better measure of central tendency. The **median** is the middle score when all the scores are arranged
in order from lowest to highest.