Nonreactive Research and Secondary Analysis
28 important questions on Nonreactive Research and Secondary Analysis
What is coding in the context of quantitative data?
- Systematically reorganizing raw data
- Converting data to a format for analysis
- Ensuring consistent application of rules
What are data records in computer terminology?
- Represent respondents or cases.
- Each record is for a single case.
- Composed of data fields (variables).
How are numbers used in a codebook?
- First column for numbers as IDs.
- Identifies cases such as gender or questionnaire.
- Uses placeholders for missing data.
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What is the first step in entering quantitative data?
- Code Sheet: Gather and transfer data onto a grid.
- Original source information is organized.
- Prepare for computerized data entry.
What are some methods for entering data into a computer?
- Direct-entry method: Type data without bar codes or sheets.
- Optical scan: Use a scanner for response forms.
- Bar code: Use a bar-code reader for data entry.
Describe possible code cleaning.
- Check categories for logical errors.
- Example: Verify gender coding (1 = Male, 2 = Female).
How does contingency cleaning ensure data accuracy?
- Look for logically impossible combinations.
- Cross-classify variables, e.g., education level and occupation.
What is the first step if you find coding errors?
- Recheck all coding for accuracy.
- Correct any identified mistakes.
How can you modify data with coding?
- Create refined categories.
- Example: Convert income data into broader categories.
What is a frequency polygon?
- Shows frequency against scores
- Used to visualize data distribution
What are measures of central tendency used for?
- Summarize information about data
- Focus on center of data distribution
How is a skewed distribution described?
- More cases at one end
- May have extreme high or low scores
How do percentiles function in a distribution?
- A percentile shows a score's specific position.
- The 25th percentile means 25% score lower.
- Median is the 50th percentile.
What is a common measure of dispersion?
- Standard deviation is the most comprehensive measure.
- It indicates average distance between scores and mean.
Why is standard deviation valuable by itself?
- Useful for comparison purposes.
- Shows average dispersion of data points from the mean.
What is the purpose of univariate techniques?
- Describe one variable.
- Techniques: frequency distribution, measures of central tendency, standard deviation, z-score.
What is the purpose of bivariate techniques?
- Describe a relationship between two variables.
- Techniques: correlation, percentage table, chi-square.
What is the purpose of multivariate techniques?
- Describe relationships among several variables.
- Techniques: elaboration paradigm, multiple regression.
What does statistical significance tell us?
- Indicates the likelihood of results happening by chance.
- Does not prove results with certainty.
What are levels of statistical significance?
- Expressed in specific levels: .05, .01, .001.
- Indicate the probability of results due to chance.
What does a .05 level of significance mean?
- 5% chance results are due to random factors.
- 95% confidence results represent the population.
Why is probability theory important in statistics?
- Helps predict outcomes over many instances.
- Provides a basis for making precise predictions.
What does statistical significance focus on regarding research results?
- Whether chance factors produced the results
- Used to determine true relationships
- Common level: 0.05
What are Type I and Type II errors?
- Type I Error: Rejects a true null hypothesis
- Type II Error: Accepts a false null hypothesis
Why is the 0.05 level commonly used in research?
- Scientifically agreed standard
- 95% confidence in results for most purposes
What dilemma arises when deciding between Type I and Type II errors?
- Trade-off in error likelihood
- Accepting a null hypothesis falsely or vice versa
How is the chi-square (χ²) test used in data analysis?
- Descriptive: Association strength
- Inferential: Chance probability
- Used to assess variables’ association
What does "independence" mean in a chi-square test?
- Expected vs. observed values match
- No association between variables
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