(7) Quantitative Data Analysis

What are the two main types of statistical analysis?

Descriptive statistics (summarizes data) & Inferential statistics (draws conclusions beyond the sample).

Why should data analysis decisions be made before data collection?

To ensure appropriate measurement methods are used and prevent data limitations.

What are the three types of variables?

Nominal (categories, no order), Ordinal (ordered categories), Interval/Ratio (numeric values).

Give an example of each type of variable.

Nominal: Blood type. Ordinal: Education level. Interval/Ratio: Temperature

What is the purpose of descriptive statistics?

To organize and summarize data using tables, graphs, and numerical measures.

What are common ways to display descriptive statistics?

Frequency tables, bar charts, pie charts, histograms.

What is inferential statistics used for?

To make conclusions about a population based on a sample.

What does a p-value of less than 0.05 indicate?

There is less than a 5% chance that the results are due to random variation, meaning they are statistically significant.

What are the common methods for dealing with missing data?

Using means, midpoints, regression predictions, or coding missing values (e.g., 999).

What does univariate analysis examine?

A single variable at a time.

What types of charts are used for nominal and ordinal data?

Nominal/Ordinal: Bar charts, pie charts. Interval/Ratio: Histograms.

What are the three measures of central tendency?

Mean: Average. Median: Middle value. Mode: Most frequent value.

Which measure of central tendency is most affected by outliers?

Mean (because extreme values can distort the average).

Which measure of central tendency is best for skewed distributions?

Median (since it is not affected by extreme values).

What are the common measures of dispersion?

Range: Difference between highest and lowest value.
Standard deviation: Average spread of values around the mean.

What does a high standard deviation indicate?

More variation in the data.

What is bivariate analysis?

The study of relationships between two variables.

What is Pearson’s r used for?

Measuring correlation between two interval/ratio variables.

What is Spearman’s rho used for?

Measuring correlation between two ordinal variables.

What statistical test is used for two categorical variables?

Chi-square test.

What is a null hypothesis?

A statement that there is no relationship between variables.

What happens if the p-value is below 0.05?

The null hypothesis is rejected, meaning the relationship is statistically significant.

What is the difference between Type I and Type II errors?

Type I error: Rejecting a true null hypothesis (false positive).
Type II error: Failing to reject a false null hypothesis (false negative).

What is multivariate analysis used for?

Examining relationships between three or more variables.

What is multiple regression analysis used for?

Predicting how multiple independent variables affect a dependent variable.

What does R² tell us in regression analysis?

The proportion of variance in the dependent variable explained by the independent variables.

What are some questions to ask when assessing a study’s statistical validity?

Were the right tests used? Was the sample randomly selected? Were assumptions about causality made?

What is the difference between statistical and practical significance?

Statistical significance: The result is unlikely due to chance. Practical significance: The result is meaningful in a real-world context.