The document provides an introduction to key concepts in statistical methodology, including: 1) Statistics are used to organize and summarize information and determine valid conclusions based on results. 2) A population is the set of all individuals of interest, while a sample is a subset selected to represent the population. 3) Parameters describe populations using measurements of all individuals, while statistics describe samples using measurements of subset individuals. 4) Data are individual measurements or observations of variables, which are characteristics that can be determined for each population member.

1. Statistics in Behavioral
Sciences
Lecture 1. Introduction to Statistical Methodology
PSY 055

2. Statistics, Science and Observations
“Statistics” means “statistical
procedures”
Uses of Statistics
• Organize and summarize information
• Determine exactly what conclusions
are justified based on the results that
were obtained.

4. Population and Samples
Population
•The set of all the individuals of
interest in a particular study.
•“Population of interest”
•Vary in size; often quite large.

5. Population and Samples
What if you can not study the population of
interest?
• Vary in size; often quite large.
• Population of all depressed patients.
• Population of all gun violence victims.
• Population of all registered voters in the
Philippines.

6. Population and Samples
Sample
•A set of individuals selected from
a population.
•Usually intended to represent the
population in a research study.

8. Parameters and Statistics
Parameters
• A value, usually a numerical value, that
describes a population.
• Derived from measurements of the
individuals in the population.

9. Parameters and Statistics
Statistics
• A value, usually a numerical value, that
describes a sample.
• Derived from measurements of the
individuals in the sample.

10. Parameters and Statistics
Parameter: Population &
Sample: Statistics
• Rarely able to study
population of
interest(Parameter).
• Makes interferences based on
sample statistics
instead(Statistics).
• Sample mean becomes the
best guess of population
mean.

11. Data and Variable
• A datum (singular)
• A single measurement or observation.
• Commonly called a score or raw score
• Data (plural)
• Measurements or observations of a variable.
• Data set
• A collection of all measurements or
observations.

12. Data and Variable
• A variable, or random variable, is a characteristic or
measurement that can be determined for each member
of a population.
• Variables may be numerical or categorical.
• Numerical variables take on values with equal units
such as weight in pounds and time in hours.
• Categorical variables place the person or thing into a
category.

13. Descriptive and Inferential Statistics
Descriptive statistics
• Focus on describing the visible
characteristics of a dataset (a population or
sample)
• Summarize, Organize, and Simplify Data
• Tables, Graphs, Averages

14. Descriptive and Inferential Statistics
Inferential statistics
• Study samples to make generalizations
about the populations
• Interpret the Experimental Data
• Common Terminology
• “Margin of error”
• “Statistically significant”

16. Illustration:
We want to know the average (mean) amount of money first-year
college students spend at ABC College on school supplies that do not
include books. We randomly surveyed 100 first-year students at the
college. Three of those students spent $150, $200, and $225,
respectively.
Given the above situation, determine the following:
POPULATION: __________________________________
SAMPLE: ______________________________________
PARAMETER: ___________________________________
STATISTIC: _____________________________________
VARIABLE: _____________________________________
DATA: _________________________________________

17. Statistical Notation
•Scores are referred to as X and Y.
•N is the number of scores in the
population.
•n is the number of scores in the
sample.