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.
3.
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.
7.
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”
15.
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.
