Chapters 1-3 Flashcards
Variable
is any characteristic of a person or thing that can be assigned a number or category.
Variables: are things that we measure, control, or manipulate in study.
observational unit
The person or thing to which the number or category is assigned.
Data
consist of the numbers or categories recorded for the observational unit.
Variability
refers to the phenomenon of a variable taking on different values or categories from observational unit to observational unit.
Quantitative Variable:
measures a numerical characteristic. Examples: Height, age, GPA, salary, temperature, area, volume, Any variable that is not quantitative is categorical.
Categorical variables
take a value that is one of several possible categories. As naturally measured, categorical variables have no numerical meaning.
Examples: Hair color, gender, field of study, political affiliation, status of disease infection.
Binary variables
are categorical variables which only two possible categories. Example: yes – no, Male/F
Research question:
looks for patterns in a variable,
compares a variable across different groups
looks for a relationship between variables.
Summary
A variable is a characteristic that varies from person to person or from thing to thing. The person or thing is called an observational unit.
Variables can be classified as categorical or quantitative.
A categorical variable with only two possible categories is called binary.
Distribution:
refers to the representation of the data. Pattern of variability of the data.
Dotplot
consists of a graph in each data value is plotted as a point (or dot) along a scale of values. It is useful for displaying the distribution of relatively small datasets of a quantitative variable.
Bar graph:
display the distribution of a categorical variable.
parameter:
numerical measurement of characteristics of a population.
Statistic:
numerical measurement of characteristics of a sample.
Explanatory variable:
is the variable whose effect you want to study
Response variable:
the variable that you suspect is affected by the other variable
observational study
observes individuals and collect specific characteristics (variables on interest) but not attempt to modify the subjects being studies
Drawing Conclusions from Studies
observational study: you can not draw a cause-and –effect conclusion between the explanatory variable and response variable.
A Confounding variable
is one whose effect on the response variable cannot be distinguished from the effect of the explanatory variable.
