Bio statistics
The mean is the average of the 4 numbers: 2 + 2 + 4 + 8/4 = 16/4 = 4.
The median is the middle value. Because there are 4 numbers, there is no true middle value.
Therefore, take the average between the two middle numbers (2 and 4). The median = 3.
The mode is 2, because the number 2 appears twice (more times than any other value).
Remember that in a normal distribution, mean = median = mode.
13. What is a skewed distribution? How does it affect mean median and mode?
A skewed distribution implies that the distribution is not normal; in other words, the data do
not conform to a perfect bell-shaped curve. Positive skew is an asymmetric distribution with an
excess of high values; in other words, the tail of the curve is on the right (mean > median >
mode). Negative skew is an asymmetric distribution with an excess of low values; in other
words, the tail of the curve is on the left (mean < median < mode). Because they are not normal
distributions, standard deviation and mean are less meaningful values.
Positive skew. An excess of higher values
makes this a non-normal distribution.
14. Define test reliability. How is it related to precision? What reduces reliability?
Practically speaking, the reliability of a test is synonymous with its precision. Reliability
measures the reproducibility and consistency of a test. For example, if the test has good inter-rater
reliability, the person taking the test will get the same score if two different people administer the
same test. Random error reduces reliability and precision (e.g., limitation in significant figures).
15. Define test validity. How is it related to accuracy? What reduces validity?
Practically speaking, the validity of a test is synonymous with its accuracy. Validity measures
the trueness of measurement; in other words, whether the test measures what it claims to measure.
For example, if you give a valid IQ test to a genius, the test should not indicate that he or she is
retarded. Systematic error reduces validity and accuracy (e.g., when the equipment is miscalibrated).
16. Define correlation coefficient. What is the range of its values?
A correlation coefficient measures to what degree two variables are related. The value of the
correlation coefficient ranges from -1 to +1.
17. True or false: A correlation coefficient of -0.6 is a stronger correlation coefficient than
+0.4.
True. The important factor in determining the strength of the relationship between the two
variables is the distance of the value from zero. A zero correlation equals no association whatso-
ever; the two variables are totally unrelated. Positive 1 equals a perfect positive correlation (when
one variable increases, so does the other), whereas negative 1 equals a perfect negative correla-
tion (when one variable increases, the other decreases). Therefore use the absolute value to give
you the strength of the correlation (e.g., -0.3 is equal to +0.3).
18. Define confidence interval. Why is it used?
When you take a set of data from a subset of the population and calculate its mean, you want
to say that it is equivalent to the mean of the whole population. In fact, however, the two means
