Exploratory Data Analysis Quiz

To perform formal hypothesis testing

To ensure data meets parametric test assumptions

To create visualizations for data presentation

To collect raw data from experiments

ANOVA

Kruskal-Wallis test

Mann-Whitney U test

Chi-square test

The steps for conducting a t-test

The process of data transformation

The requirements for non-parametric tests

The likelihood of data falling within specific standard deviations

The data is drawn from a normal distribution

The data has equal variances

The data is skewed

The data contains outliers

Mann-Whitney U test

ANOVA

Levene's Test

Shapiro-Wilk Test

The sample size is too small

The data is normally distributed

There is a problem with homogeneity of variance

The variances across groups are equal

It ensures data is collected accurately

It eliminates outliers from the dataset

It modifies the data to fit a normal distribution

It increases the sample size

Bell curve

Presence of multiple modes

Skewness of zero

Symmetrical shape

The asymmetry of the data distribution

The spread of the data

The number of outliers present

The average value of the data

Data is heavily skewed

Data contains many outliers

Data is uniformly distributed

Data likely follows a normal distribution