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Summary Psychology 253 Short Summaries
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Psychology 253 Short Summaries, chapters 1-6, great for a quick recap on each chapter, covers all the important points in each chapter, best used for the test
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Statistics For The Behavioral Science Notes
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Solution Manual for Essentials Of Statistics For The Behavioral Sciences 10th Edition Frederick J Gravetter, Larry B. Wallnau, Lori Ann B. Forzano, James E. Wi
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Solution Manual for Essentials Of Statistics For The Behavioral Sciences 10th Edition Frederick J Gravetter, Larry B. Wallnau, Lori Ann B. Forzano, James E. Wi
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DARYAN VDW ÓPSYCHOLOGY 253 SUPER SUMMARIES
CHAPTER ONE
1. The term statistics is used to refer to methods for organizing, summarizing, and interpreting
data.
2. Scientific questions usually concern a population, which is the entire set of individuals one
wishes to study. Usually, populations are so large that it is impossible to examine every
individual, so most research is conducted with samples. A sample is a group selected from
a population, usually for purposes of a research study.
3. A characteristic that describes a sample is called a statistic, and a characteristic that
describes a population is called a parameter. Although sample statistics are usually
representative of corresponding population parameters, there is typically some
discrepancy between a statistic and a parameter. The naturally occurring difference
between a statistic and the corresponding parameter is called sampling error.
4. Statistical methods can be classified into two broad categories: descriptive statistics,
which organize and summarize data, and inferential statistics, which use sample data to
draw inferences about populations.
5. A construct is a variable that cannot be directly observed. An operational definition
measures and
6. defines a construct in terms of external behaviors that are representative of the construct.
7. A discrete variable consists of indivisible categories, often whole numbers that vary in
countable steps. A continuous variable consists of categories that are infinitely divisible
and each score corresponds to an interval on the scale. The boundaries that separate
intervals are called real limits and are located exactly halfway between adjacent scores.
8. A measurement scale consists of a set of categories that are used to classify individuals. A
nominal scale consists of categories that differ only in name and are not differentiated in
terms of magnitude or direction. In an ordinal scale, the categories are differentiated in
terms of direction, forming an ordered series. An interval scale consists of an ordered
series of categories that are all equal-sized intervals. With an interval scale, it is possible to
differentiate direction and distance between categories. Finally, a ratio scale is an interval
scale for which the zero point indicates none of the variable being measured. With a ratio
scale, ratios of measurements reflect ratios of magnitude.
9. The experimental method examines relationships between variables by manipulating an
independent variable to create different treatment conditions and then measuring a
dependent variable to obtain a group of scores in each condition. The groups of scores
are then compared. A systematic difference between groups provides evidence that
changing the independent variable from one condition to another also caused a change in
the dependent variable. All other variables are controlled to prevent them from influencing
the relationship. The intent of the experimental method is to demonstrate a cause-and-
effect relationship between variables.
10. Nonexperimental studies also examine relationships between variables by comparing
groups of scores, but they do not have the rigor of true experiments and cannot produce
cause-and-effect explanations. Instead of manipulating a variable to create different
groups, a nonexperimental study uses a pre-existing participant characteristic (such as
male/female) or the passage of time (before/after) to create the groups of scores being
compared.
11. In an experiment, the independent variable is manipulated by the researcher and the
dependent variable is the one that is observed to assess the effect of the treatment. The
1
, DARYAN VDW Ó
12. variable that is used to create the groups in a non-experiment is a quasi-independent
variable.
13. The letter X is used to represent scores for a variable. If a second variable is used, Y
represents its scores. The letter N is used as the symbol for the number of scores in a
population; n is the symbol for a number of scores in a sample.
14. The Greek letter sigma (S) is used to stand for summation. Therefore, the expression SX is
read “the sum of the scores.” Summation is a mathematical operation (like addition or
multiplication) and must be performed in its proper place in the order of operations;
summation occurs after parentheses, exponents, and multiplying/dividing have been
completed.
CHAPTER TWO
1. The goal of descriptive statistics is to simplify the organization and presentation of data. One
descriptive technique is to place the data in a frequency distribution table or graph that shows
exactly how many individuals (or scores) are located in each category on the scale of
measurement.
2. A frequency distribution table lists the categories that make up the scale of measurement (the
X values) in one column. Beside each X value, in a second column, is the frequency or number
of individuals in that category. The table may include a proportion column showing the relative
frequency for each category:
!
Proportion à p =
"
The table may include a percentage column showing the percentage associated with
each X value:
!
Percentage à p (100) = (100)
"
3. It is recommended that a frequency distribution table have a maximum of 10 to 15 rows to
keep it simple. If the scores cover a range that is wider than this suggested maximum, it is
customary to divide the range into sections called class intervals. These intervals are then
listed in the frequency distribution table along with the frequency or number of individuals
with scores in each interval. The result is called a grouped frequency distribution. The
guidelines for constructing a grouped frequency distribution table are as follows:
• There should be about 10 intervals.
• The width of each interval should be a simple number (e.g., 2, 5, or 10).
• The bottom score in each interval should be a multiple of the width.
• All intervals should be the same width, and they should cover the range of
scores with no gaps.
4. A frequency distribution graph lists scores on the horizontal axis and frequencies on the
vertical axis. The type of graph used to display a distribution depends on the scale of
measurement used. For interval or ratio scales, you should use a histogram or a polygon.
For a histogram, a bar is drawn above each score so that the height of the bar corresponds
to the frequency. Each bar extends to the real limits of the score, so that adjacent bars
touch. For a polygon, a dot is placed above the midpoint of each score or class interval so
that the height of the dot corresponds to the frequency; then lines are drawn to connect the
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