Statistics: Key Vocabulary from Lecture 1 ai cards

Vocabulary flashcards covering core statistical concepts from the lecture notes.

Statistics

A collection of methods for planning experiments, obtaining data, and then organizing, summarizing, analyzing, interpreting, presenting, and drawing conclusions based on the data.

Population

The complete collection of all elements to be studied (scores, measurements, people, etc.).

Census

The collection of data from every member of the population.

Sample

A subcollection of members selected from part of the population.

Parameter

A measurement describing a characteristic of a population (the result from a census).

Statistic

A measurement describing a characteristic of a sample.

Qualitative data

Also called categorical data; data that describe categories or labels rather than numbers.

Quantitative data

Data that are numerical and represent counts or measurements.

Discrete data

Quantitative data that are counted and have distinct, separated values (finite or countably infinite).

Continuous data

Quantitative data that can take any value within an interval, including decimals.

Nominal level of measurement

Categorical data with no natural order; categories are simply labels.

Ordinal level of measurement

Categorical data with a natural order, but differences between values are not necessarily meaningful.

Interval level of measurement

Quantitative data that are ordered with meaningful differences but with no true zero.

Ratio level of measurement

Quantitative data with ordered values, meaningful differences, and a true zero, allowing ratios.

Frequency distribution

A table or chart showing how data are partitioned among categories by listing categories and their frequencies.

Frequency table

A table listing categories together with the number of data values in each category.

Bias

Systematic error in sampling or data collection; bias occurs when the data are not independent or representative (e.g., self-selected volunteers).

Statistical significance

A result is statistically significant if it is unlikely to occur by chance under the null hypothesis.

Practical significance

Whether the size of an effect is large enough to be of real-world importance, beyond statistical significance.

Data collection method: Survey

A method of collecting data by asking a sample of individuals or groups.

Outlier

A data point that lies far away from the rest of the data values.

Process: Prepare, Analyze, Conclude

Steps in a statistical study: Prepare the context and goal, analyze and explore the data, and conclude by evaluating significance and implications.

True or False: A frequency distribution lists every individual data value in its raw form without grouping.

False. A frequency distribution organizes data into categories and shows how often each category occurs, rather than listing raw individual values unorganized.

Which term best describes a data point that is significantly distant from the other observations in a dataset?

a) Outlier

a) Outlier

b) Bias

c) Parameter

d) Sample

True or False: In the statistical study process 'Prepare, Analyze, Conclude', the 'Prepare' stage includes exploring and examining the data for patterns.

False. Exploring and examining data is part of the 'Analyze' stage. The 'Prepare' stage focuses on context and goals.

True or False: The time it takes for a commuter to travel to work is typically considered discrete data.

False. Time is continuous data because it can take any value within an interval (e.g., 25.7 minutes, 30.15 seconds).

What is a common data collection method where information is gathered by asking questions to a group of individuals?

A Survey