📖 Statistical Analysis – Q&A Study Set

Descriptive vs. Inferential

Q: What is the main purpose of descriptive statistics?

A: To summarize and organize data so it’s easier to interpret (e.g., mean, median, mode, SD).

to summarize and organize data so it’s easier to understand

Descriptive vs. Inferential

Q: What is the main purpose of inferential statistics?

A: To make conclusions about a population based on sample data (e.g., t-test, ANOVA).

to use data from a sample to make conclusions or predictions about a larger population.

Distributions

Q: What is a distribution?

A: A frequency count of scores or attributes.

the way data values are spread out or arranged, showing how often each value occurs.

Distributions

Q: Name two common graphs used to show distributions.

A: Histogram and bar chart.

Distributions

Q: What does a mesokurtic distribution mean?

A: A normal, bell-shaped curve.

Central Tendency

Q: Which measure of central tendency is most affected by outliers?

A: The mean.

Central Tendency

Q: Which measure is best for skewed distributions?

A: The median.

Central Tendency

Q: Which measure is best for categorical data?

A: The mode.

Variability

Q: What does standard deviation tell us?

A: How spread out the scores are around the mean.

Variability

Q: If all values in a group are the same, what is the SD?

A: Zero.

Normal Curve

Q: What percentage of data falls within ±2 SD of the mean?

A: About 95%.

Normal Curve

Q: Why are normal curves important for parametric statistics?

A: Many tests assume normally distributed data.

because many parametric tests assume data follows a normal distribution, which allows accurate predictions, comparisons, and probability calculations.

Levels of Measurement

Q: Give an example of nominal data.

A: Pass/fail; type of error.

Levels of Measurement

Q: What level of measurement includes true zero?

A: Ratio (e.g., vowel duration, Hz).

Levels of Measurement

Q: What level of measurement are severity ratings (mild, moderate, severe)?

A: Ordinal.

Parametric vs. Nonparametric

Q: When do you use parametric tests?

A: When data are normal, interval/ratio, and variances are equal.

Parametric vs. Nonparametric

Q: When do you use nonparametric tests?

A: When data are skewed or ordinal/nominal.

Analyzing Differences

Q: What test compares two groups with small samples?

A: t-test.

Analyzing Differences

Q: What test compares more than two groups?

A: ANOVA.

Analyzing Differences

Q: What do post hoc tests show?

A: Which specific group differences are significant.

Post hoc tests show which groups are different from each other after the main test says there is a difference.

(like ANOVA).

Significance Testing

Q: What does alpha (α) represent?

A: Probability of making a Type I error (rejecting null when it’s true).

Alpha (α) represents the significance level, or the probability of making a Type I error — rejecting the null hypothesis when it is actually true.

Significance Testing

Q: What’s the conventional alpha for exploratory studies?

A: 0.05.

Significance Testing

Q: What’s the difference between one-tailed and two-tailed tests?

A: One-tailed - directional prediction; two-tailed - nondirectional.

Significance Testing

Q: Does statistical significance mean clinical significance?

A: No, a statistically significant result may not be meaningful in practice.

Correlation & Regression

Q: What does Pearson’s r measure?

A: The strength and direction of the relationship between two interval/ratio variables.

Pearson’s r measures the strength and direction of the linear relationship between two variables.

Correlation & Regression

Q: What does r² represent?

A: Percent of variance shared between two variables.

Correlation & Regression

Q: What is regression used for?

A: Predicting an outcome variable using one or more predictor variables.

Effect Size & Power

Q: What is Cohen’s d?

A: An effect size that measures the difference between two group means in SD units.

Effect Size & Power

Q: What value of Cohen’s d is considered large?

A: 0.80.

Effect Size & Power

Q: What does power analysis determine?

A: The sample size needed to detect an effect at a given alpha level.

Graphs & Results

Q: When should you use a bar graph?

A: To show group differences in means, percentages, or frequencies.

Graphs & Results

Q: When should you use a line graph?

A: To show changes over time, trends, or interactions.