Intro to Stats for the Behavioral Sciences

1. Introduction to
Statistics for the
Behavioral Sciences

2. Statistics
 It the practice or science of collecting and
analyzing numerical data in large quantities,
especially for the purpose of inferring
proportions in a whole from those in a
representative sample.

3. Statistics
Branches of Statistics
Descriptive
-organizes, summarizes, and
communicates a group of
numerical observations.
Inferential
-uses
sample data to make general
estimates about the larger
population.

4. Statistics
• Observations drawn from a population of
interest. It is described by a statistic.
Sample
• All possible observations about which we
would like to know. It is described by a
parameter.
Population

5. Sampling Techniques
 Random Sampling – every member of a
population has an equal chance of being
selected.
 Systematic Sampling – taking the nth element from
a given list.
 Stratified Sampling – division according to
categories
 Cluster Sampling – the population is divided into
clusters where samples are extracted.

6. Sampling Techniques
 Non-random Sampling –recruitment of
participants occur all of a sudden as the researcher
may ought them to be useful despite of being
unable to generalize the results found from such
sample
 Convenience Sampling – direct selection of participants until the
desirable amount is reached by the researcher
 Quota Sampling – similar to convenience sampling, but it ensures
equal representativeness.
 Snowball Sampling – a sampling based on recommendations.
 Purposive Sampling – a sampling based on the knowledge of a
given population and the research objective.
 Self-selected Sampling – a sampling based on the desire of the
people to identify themselves with the population being studied.

7. Variables
 It is any observation of a physical,
attitudinal, or behavioral characteristic that
can take on different values

8. Variables
• Can take on only specific values (e.g., whole
numbers); no other values can exist between
these numbers.
Discrete
• can take on a full range of values (e.g., numbers
out to several decimal places); an infinite
number of potential values exists.
Continuous

9. Variables and Research
• at least two levels that we either manipulate or observe to
determine its effects
Independent Variable
• The outcome variable that we hypothesize to be related to, or
caused by, changes
Dependent Variable
• systematically varies with the independent variable so that we
cannot logically determine which variable is at work
Confounding Variable

10. Levels of Measurement
• variable used for observations that have categories, or names, as their values
Nominal
• variable used for observations that have rankings (i.e., 1st, 2nd, 3rd, . . .) as
their values.
Ordinal
• variable used for observations that have numbers as their values; the distance
(or interval) between pairs of consecutive numbers is assumed to be equal.
Interval
• a variable that meets the criteria for an interval variable but also has a
meaningful zero point.
Ratio