module 16 Flashcards
Its purpose is to gather useful information to find solutions to research questions of interest
data analysis
may be used to:
- Describe data sets
- Determine the degree of relationship of variables
- Determine differences between variables
- Predict outcomes
- Compare variables
Data Analysis
- Used for labeling variables.
- Sometimes called “categorical data.”
- Example is the “Yes or No Scale.”
nominal scale
- Assigns order on items on the characteristics to be measured.
- Involves the ranking of individuals, attitudes, and characteristics.
- Example is the “Strongly Agree, Agree, Disagree, or Strongly Disagree Scale.”
ordinal scale
- Has equal units of measurements, thereby, making it possible to interpret the order scale scores and the distance between them.
- Do not have a “true zero.”
interval scale
- Considered the highest level of measurement.
- Has the characteristics of an interval scale but it has a zero point.
ratio scale
Tests look for an association between variables.
correlation
Tests for the strength of the association between two continuous variables.
pearson correlation
Tests for the strength of the association between two ordinal variables.
spearman correlation
Tests for the strength of the association between two categorical variables.
chi-square
Look for the difference between the means of variables.
comparison of means
Tests for difference between two related variables.
paired T-test
Tests for difference between two independent variables.
independent T-test
Tests the difference between group means after any other variance in the outcome variable is accounted for.
ANOVA
Assess if change in one variable predicts change in another variable.
regression
Tests how change in the predictor variable predicts the level of change in the outcome variable.
simple regression
Tests how change in the combination of two or more predictor variables predict the level of change in the outcome variable.
multiple regression
- Used when you are comparing two or more groups.
Hypothesis Testing
- When evaluating this, you need to account for both the variability in your sample and how large your sample is.
Hypothesis Testing
- Make an assessment of whether any differences you see are meaningful or if they are likely just due to chance.
Hypothesis Testing
- Uses a test statistic that compares groups or examines associations between variables.
Hypothesis Testing
Statement of no effect, relationship, or difference between two or more groups or factors.
null hypothesis
- Statement that there is an effect or difference.
- Usually the hypothesis the researcher is interested in proving.
alternative hypothesis
