Study Guide for Exam I
Chapters 1 through 4
Chapter 1
1. What are the characteristics of a population and sample? What is an example of each?
2. What are dependent and independent variables? What variable is manipulated? What variable is the
outcome?
3. Define inferential and descriptive statistics.
4. Are you able to determine causality using correlational methods? If not, why?
5. Describe the three techniques to control other variables in experimental designs.
6. What is a nonequivalent group methodology? What is a quasi-independent variable? Give an example.
7. Be able to understand continuous and discrete variables.
8. Identify, describe, and give examples of the four scales of measurement.
9. What is a construct and operational definition? What are the two components of an operational
definition?
Chapter 2
1. Be able to construct a frequency and grouped frequency distribution table.
2. Be able to create a histogram, modified histogram, polygon, bar graph, and stem-and-leaf.
3. Be able to identify the shape of frequency distributions including symmetrical and skewed.
4. Know where the mean, median and mode are located for positively and negatively skewed
distributions.
5. Be able to identify whether a distribution is positively or negatively skewed based on the frequency
distribution or the shape of the distribution.
Chapter 3
1. Know the characteristics associated with mean, median, and mode. Know how to calculate each of
these central tendencies. Know when to use the mean, median, and mode as well as the disadvantages of
using each.
2. Understand how the mean, median, and mode look on negatively and positively skewed distributions.
Chapter 4
1. What is variability?
2. What is standard deviation? Know how to calculate the standard deviation. Know how variance relates
to standard deviation. Know how to calculate the variance.
3. Understand the different formulas to calculate sum of squared deviations (SS). Know how to calculate
these different formulas (e.g., definition, computational).
4. Know the different formulas for calculating standard deviation and variance among both populations
and samples.
5. Understand why the formulas to calculate standard deviation and variance are different among
populations and samples.
6. Be able to calculate the standard deviation and variance for a population and sample.