Population
the whole group,
ex; # of BEC1 students
Parameter
characteristic of the population
ex; mean (average) age of BEC1
... [Show More] students
00:00
01:42
Sample
- a group taken from the population, needs to represent population well
- used because it is too expensive/tiring to use entire population
Statistic
numerical/data about population
ex; mean, median, mode, standard deviation, variance
inferential statistics
- Techniques that allow conclusions to be drawn about the relationships found among different variables in a population sample are referred to as
- They are used to examine relationships between variables in a data set, how one variable is related to other variables
- They are used to see how well sample data can be generalized to the population.
- ex; chi-square test, t test, the one-way ANOVA
descriptive statistics
- They are numerical or graphical summaries of data
- may include charts, graphs, and simple summary statistics such as means and standard deviations to describe characteristics of a population sample.
Example of Descriptive Questions
- What is the level of intention to engage in physical activity among a group of adults who recently joined a fitness facility?
- What is the actual level of physical activity among a group of adults that recently joined a fitness facility?
Example of Inferential Questions
- Does attitude toward exercise affect participation in physical activity?
- Does the extent to which participants perceive themselves as able to exercise (perceived behavioral control) affect participation in physical activity?
- Do subjective norms affect participation in physical activity?
- Does intention to exercise predict physical activity?
Explanatory studies
- Studies that have the primary purpose of elucidating the relationships among variables
- depend on inferential questions
Quantitative Variable
measures quantity
ex; BP, weight, height
Categorical Variable
measures quality
ex; age, gender, marital status
Prediction and Control Studies
seek to determine which variables are predictive of other variables and to determine causality (e.g., one event causes another to happen)
Quasi-experimental or Experimental Study Designs
- How data for prediction and control studies are typically collected
- researchers introduce an intervention (e.g., change one of the variables being examined)
- thought to have better validity, making causal inference more solid than with purely observational study designs
- include random selection and random assignment of study participants to either the intervention group or to one or more control groups that do not receive the intervention or treatment [Show Less]