Chapter 1 Wrap-Up
Concept Check
Take this quiz to check your comprehension of this chapter.
If you are using an offline version of this text, access the quiz for this chapter via the QR code.
Section Resources
If you are using an offline version of this text, access these materials by visiting https://doi.org/10.7294/26207456.
1.1 Introduction to Statistics and Key Terms
1.3 Data Collection and Observational Studies
Key Terms
Try to define the terms below on your own. Check your response by scrolling over the term, or looking at the end-of-book glossary!
1.1 Introduction to Statistics and Key Terms
- Data analysis process
- Descriptive statistics
- Inferential statistics
- Probability
- Population
- Parameters
- Sample
- Statistic
- Individuals
- Variable
- Values
- Data
1.2 Data Basics
- Qualitative (categorical)
- Quantitative (numerical)
- Discrete
- Continuous
- Nominal scale
- Ordinal scale
- Interval scale
- Ratio scale
- Variation
- Data analysis
1.3 Data Collection and Observational Studies
- Explanatory variable
- Response variable
- Anecdotal evidence
- Observational studies
- Designed (controlled) experiments
- Associations
- Confounding (lurking, conditional) variable
- Prospective study
- Retrospective study
- Cohort study
- Longitudinal study
- Cross-sectional study
- Case-control study
1.4 Designed Experiments
- Treatments
- Experimental unit
- Repeated measures
- Control group
- Placebo
- Blinding
- Double-blind
- Factors
- Levels
- Treatment combinations (interactions)
- Completely randomized
- Block design
- Matched pairs design
1.5 Sampling Techniques and Ethics
- Simple random sample (SRS)
- Stratified sampling
- Cluster sampling
- Systematic sampling
- Sampling bias
- Sampling variability
- Convenience sampling
Extra Practice
Extra practice problems are available at the end of the book (Chapter 1 Extra Practice).
Process of collecting, organizing, and analyzing data
Methods of organizing, summarizing, and presenting data
The facet of statistics dealing with using a sample to generalize (or infer) about the population
The study of randomness; a number between zero and one, inclusive, that gives the likelihood that a specific event will occur
The whole group of individuals who can be studied to answer a research question
A number that is used to represent a population characteristic and can only be calculated as the result of a census
A subset of the population studied
A number calculated from a sample
The person, animal, item, place, etc. about which we collect information
A characteristic of interest for each person or object in a population
Possible observations of the variable
Actual values (numbers or words) that are collected from the variables of interest
Data that describes qualities or puts individuals into categories; also known as categorical data
Numerical data with a mathematical context
A random variable that takes on a countable amount of values
A random variable (RV) whose outcomes are measured as an uncountable, infinite number of values
Categorical data where the the categories have no natural, intuitive, or obvious order
Categorical data where the the categories have a natural or intuitive order
Quantitative data where the difference or gap between values is meaningful
Quantitative data where the difference or gap between values is meaningful AND has a true 0 value
The level of variability or dispersion of a dataset; also commonly known as variation/variability
The independent variable in an experiment; the value controlled by researchers
The dependent variable in an experiment; the value that is measured for change at the end of an experiment
Evidence that is based on personal testimony and collected informally
Data collection where no variables are manipulated
Data collection where variables are manipulated in a controlled setting
A relationship between variables
A variable that has an effect on a study even though it is neither an explanatory variable nor a response variable
Collecting information as events unfold
Collecting or using data after events have taken place
Longitudinal study where a group of people (typically sharing a common factor) are studied and data is collected for a purpose
Collecting data multiple times on the same individuals over a period of time, usually in fixed increments
Data collection on a population at one point in time (often prospective)
A study that compares a group that has a certain characteristic to a group that does not, often a retrospective study for rare conditions
Different values or components of the explanatory variable applied in an experiment
Any individual or object to be measured
When an individual goes through a single treatment more than once
A group in a randomized experiment that receives no (or inactive) treatment but is otherwise managed exactly as the other groups
An inactive treatment that has no real effect on the explanatory variable
Not telling participants which treatment they are receiving
The act of blinding both the subjects of an experiment and the researchers who work with the subjects
Variables in an experiment
Certain values of variables in an experiment
Combinations of levels of variables in an experiment
Dividing participants into treatment groups randomly
Grouping individuals based on a variable into "blocks" and then randomizing cases within each block to the treatment groups
Very similar individuals (or even the same individual) receive two different treatments (or treatment vs. control), then the results are compared
Each member of the population is equally likely to be chosen for a sample of a given sample size and each sample is equally likely to be chosen
Dividing a population into groups (strata) and then using simple random sampling to identify a proportionate number of individuals from each
A method of sampling where the population has already sorted itself into groups (clusters), and researchers randomly select a cluster and use every individual in the chosen cluster as the sample
Using some sort of pattern or probability-based method for choosing your sample
Bias resulting from all members of the population not being equally likely to be selected
The idea that samples from the same population can yield different results
Selecting individuals that are easily accessible and may result in biased data
