Essentials of Statistics - Chapter 1: Introduction to Statistics

Flashcards summarizing key concepts from Chapter 1 of Essentials of Statistics, focusing on definitions, examples, and differences in statistical methods.

What are the key steps involved in the statistical study process?

Prepare, Analyze, Conclude.

What does statistics involve?

The science of planning, organizing, analyzing, and interpreting data.

What is the difference between a population and a sample?

A population is the complete collection of data; a sample is a subcollection selected from a population.

What is a census?

The collection of data from every member of a population.

What is a voluntary response sample?

A sample where respondents decide whether to be included, often leading to biased results.

What is the difference between statistical significance and practical significance?

Statistical significance relates to the likelihood of an event occurring by chance; practical significance considers if the effect is large enough to be meaningful in real life.

What is quantitative data?

Data that consists of numbers representing counts or measurements.

What is categorical data?

Data that consists of labels or categories, not numbers.

What are the four levels of measurement in statistics?

Nominal, Ordinal, Interval, and Ratio.

What is the nominal level of measurement?

Data consisting of names or categories only, with no order.

What characterizes the ordinal level of measurement?

Data that can be arranged in order, but the differences between values are meaningless.

What defines the interval level of measurement?

Data that can be arranged in order, with meaningful differences, but no true zero point.

What is the ratio level of measurement?

Data that can be arranged in order, with meaningful differences and a true zero point.

What is Big Data?

Data sets so large and complex that their analysis is beyond the capabilities of traditional software tools.

What does it mean if data is missing completely at random?

The likelihood of data being missing is independent of its value or other values in the data set.

What method can be used to correct for missing data?

Impute Missing Values, which involves substituting values for the missing data.

What differentiates an experiment from an observational study?

In an experiment, a treatment is applied to observe effects, while in an observational study, individuals are measured without modification.