First class prep: August 28
Pages 3-8 summed…..
Populations vs. Samples:
●​ Population = all individuals of interest in a study.
●​ Sample = a smaller group selected from the population to represent it.
●​ Researchers study samples but generalize results back to the population.​
Variables and Data:
●​ Variable = anything that can change (like height, mood, temperature).
●​ Datum (score) = a single measurement.
●​ Data = the full set of scores or measurements.​
Parameters vs. Statistics:
●​ Parameter = a numerical value describing a population.
●​ Statistic = a numerical value describing a sample.
●​ Research usually estimates population parameters using sample statistics.​
Types of Statistics:​
●​ Descriptive statistics: summarize, organize, and simplify data (e.g., averages, graphs).
●​ Inferential statistics: use sample data to make generalizations about a population.​
Sampling Error:​
●​ The natural difference between a sample statistic and the true population parameter.
●​ It’s unavoidable and must always be considered in research.
Vocab
-​ Statistics: a set of mathematical procedures for organizing,
summarizing, and interpreting information.
-​ Sample: is a set of individuals selected from a population, usually intended to
represent the population in a research study.
-​
Population: is the set of all the individuals of interest in a particular study.
-​ Variable: a characteristic or condition that changes or has different values
for different individuals.
-​
Data: measurements or observations
-​
Data set: a collection of
measurements or observations
-​
Datum: a single measurement or
observation and is commonly called a Score or Raw Score
-​
Parameter-: a value usually a numerical value, that describes a population.
-​
Statistic: a value: usually a numerical value, that describes a sample
-​
Descriptive statistics: are statistical procedures used to summarize, organize,
and simplify data.
-​
Inferential statistics: consist of techniques that allow us to study samples and
then make generalizations about the populations from which they were selected.
-​
Sampling error: the naturally occurring discrepancy, or error, that exists
between a sample statistic and the corresponding population parameter.