Information about Basic Statistics

Contents

Definitions
Significant Difference
Correlation
Examples

Definitions

The Three M's

Mean
The average result of a test, survey, or experiment.

Median
The score that divides the results in half--the middle value.

Mode
The most common result (the most frequent value) of a test, survey, or experiment.

N
"N" is usually used to indicate the number of subjects in a study.

Significant Difference

Significance
The measure of whether the results of research were due to chance.

p-value
The way in which significance is reported statistically (i.e. p<.01 means that there is at least a 1% chance that the results of a study are due to random chance.)

Correlation

Correlation
The degree to which two factors appear to be related.

r-value

The way in which correlation is reported statistically (a number between -1 and +1). An r-value of 0 means there is no correlation at all between the elements being studied.

Examples

Mean Example :

• Seven people take a test in which 10 points are possible. Their scores are: 4, 7, 7, 8, 9, 9, and 10.
• The average is the sum of the scores (54) divided by the number of people (7). The result is 7.71.
• In statistics, mean is the same as average. You would say for this example: "The mean score on the test is 7.71." Note, however, that no one actually received a score of 7.71 on the test.

Median Example :

• Seven people take a test in which 10 points are possible. Their scores are: 4, 7, 7, 7, 9, 10, and 10.
• A score of 7 is the middle value when the scores or put in order.
• For this example, you would say: The median score on the test is a 7."

Mode Example :

• Seven people take a test in which 10 points are possible. Their scores are: 4, 7, 7, 7, 9, 10, and 10.
• Looking at these scores, you can see that 7 is the most common score on the test because three people received a score of 7.
• For this example, you would say: "The mode score of the test is 7."
  

Significant Difference Example :

• A study had one group of students (Group A) study using notes they took in class; the other group (Group B) studied using notes they took after class using a recording of the lecture.   Students in Group A scored higher on a test than Group B. The study reports a significance of p<.01 for the results.
• This means that whatever the reason students who took notes in class did better on the test, there is only a 0 - 1% chance that the results are due to some random factor (such as Group A having smarter students than Group B).
• Note that generally, p-values need to be fairly low (.01 and .05 are common) in order for a study to make any strong claims based on the results.

Correlation Example :

• Correlation should not be confused with causation. Just because two factors are reported as being correlated, you cannot say that one factor causes the other.
• For example, you might find a correlation between going to the library at least 40 times per semester and getting high scores on tests. However, you cannot say from these findings what exactly it is about going to the library, or about people who go to libraries often, that is responsible for higher test scores.

Return to the Statistics Lesson page by closing this page.

| iStudy | Module Descriptions | Getting Access | Contacts  | FAQ