Textbook notes - applicable to spring term as well

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Published on 1 Feb 2011
School
UTSG
Department
Psychology
Course
PSY201H1
Professor
CHAPTER ONE
INTRO TO STATISTICS
1.1
Statistics: set of standardized mathematical procedures used to organize, summarize
& interpret info.
1.2
population: set of all individuals of interest in a particular study
sample: set of individuals WITHIN a population, usually selected to represent the
population in a research study.
** can also refer to scores that correspond to individuals rather than the indiv.
themselves**
Once a study is done on a sample, the goal is to generalize the results back to the
poplulation.
variable: characteristic or condition, values for different individuals or over time.
Data: measurements or observations datum = 1 data set = collection of
Score / raw score: common words for datum
Parameter : a characteristic that describes the population
usually numerical value
usually derived from measurements of individuals within population
o
ex: avg. reading score for *all 4th-graders in Texas*
**= population
\ \ \ ~~~~POPULATION PARAMETER~~~~/ / /
Statistic: a characteristic that describes a sample
usually numerical value
usually derived from measurements of individuals within sample
\ \ \ ~~~~~SAMPLE STATISTIC~~~~~/ / /
DESCRIPTIVE STATISTICS: used to summarize, organize&simplify data (raw
scores)
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INFERENTIAL STATISTICS: sample data is used to make general
statements/reach generalized conclusions about the population from which it is
selected.
Sampling error: discrepancy between sample statistic & corresponding population
parameter.
Ex: sample proportion error.
STEP-BY-STEP EXAMPLE OF STATISTICS IN IN RESEARCH
Population: first-grade children
Sample A: first-graders taught by method A
Sample B: first-graders taught by method B
1.a.Experiment: compare 2 teaching methods
b.Data: Collect test scores for students in each sample
2.Descriptive Statistics: organize & simplify
a. find average scores for each sample
b.graph
3.Inferential Statistics: interpret results
a.Compare averages: calculate difference
b.Decide whether the difference in data is due to sampling error or a
difference in the 2 methods of teaching.
1.3 DATA STRUCTURES, RESEARCH METHODS
to establish existence of relationships, measurement of two variables is necessary.
There are two data structures
I. CORRELATIONAL METHOD: measuring 2 variables for each individual, to
determine whether there is a relationship between them. Variables are not
manipulated, one group of individuals is studied
II. EXPERIMENTAL & NONEXPERIMENTAL: comparing multiple groups of
scores. 1 variable is used to define a group, and the second is measured.
Ex: 1 group is shown violent movies, the other is shown romantic comedies,
then both groups are tested for aggressive behavior.
Variable 1 = type of movie
Variable 2 = aggression
EXPERIMENTAL METHOD: demonstrate causal relationship between two
variables
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Document Summary

Statistics: set of standardized mathematical procedures used to organize, summarize. 1. 2 population: set of all individuals of interest in a particular study sample: set of individuals with in a population, usually selected to represent the population in a research study. ** can also refer to scores that correspond to individuals rather than the indiv. themselves** Once a study is done on a sample, the goal is to generalize the results back to the poplulation. variable: characteristic or condition, values for different individuals or over time. data: measurements or observations datum = 1 data set = collection of . score / raw score: common words for datum. parameter : a characteristic that describes the population: usually numerical value, usually derived from measurements of individuals within population, ex: avg. reading score for *all 4th-graders in texas* \ \ \ ~~~~ population parameter ~~~~ / / /