Exploring One–Variable Data

Bootstrap confidence interval procedure

Two-Sample T-Test

Paired Samples T-Test

One-Sample Z-Test

Variables that are kept constant or controlled in a study to eliminate their influence on the dependent variable.

Humans and other types of units, such as animals, plants, or inanimate objects, from which data can be collected.

Characteristics or attributes that are measured or observed for each individual in a study.

Individuals who contribute and answer surveys, providing information about themselves or their opinions.

Voluntary response bias

Undercoverage bias

Response bias

Nonresponse bias

Conducting a chi-square goodness-of-fit test concerning binned predicted probabilities versus observed frequencies.

Graphically inspecting scatterplots obtained from transformed versions of both sets of predictors and outcomes.

Utilizing Durbin-Watson autocorrelation errors to identify possible non-random patterns in error terms.

Performing Shapiro-Wilk normality tests on the original predictor variables to ensure they arise from normal distributions.

It can either increase or decrease Type II error rate ($\beta$), depending on other factors.

It decreases Type II error rate ($\beta$).

It increases Type II error rate ($\beta$).

It does not affect Type II error rate ($\beta$).

There is no relationship between the values.

Each value is significantly different from the mean.

The values are spread out over a wide range.

The values are relatively close to each other.

1.5

2.5

2

1

Uniform

Bell curve

Skewed left

Skewed right

The standard normal distribution has a mean of 0 and a standard deviation of 1.

The standard normal distribution can only be used for normally distributed data.

The standard normal distribution is a specific type of normal distribution.

Z-scores from the standard normal distribution can be used to compare different data sets.

Stratified random sampling

Cluster sampling

Simple random sampling

Convenience sampling