stats exam 1 study guide ACTUAL UPDATED Questions and CORRECT Answers
C
Terms in this set (129)
Data collection the process and methodology of obtaining data from a
population or sample, including survey design, experiments, and observational
studies.
Descriptive statistics methods for organizing, summarizing, and presenting data
using numerical measures, tables, and graphical displays.
Probability the mathematical framework used to quantify uncertainty and
measure the likelihood of events in a random experiment.
Inferential statistics methods of using information from a sample to draw
conclusions about the population.
Cases the people or objects included in the study.
- Respondents, subjects, participants, experimental units
Variable the characteristic of the case to be measured or observed.
- Identifier variable
Categorical variable divides cases into groups, placing eachcase into exactly one or more categories.
It consists of groups orcategory names.• Examples: Eye color, political party,
educational level
two types of Categorical variable nominal: ordering of categories does not matter
• Example: Sex, phone brand
ordinal: ordering of categories does matter
• Examples: Final grade, clothing size
, Quantitative variable measures a numerical quantity for
each case. It consists of numerical measures or counts.
• Examples: Height, temperature, number of children per family
two kinds of quantitative variable discrete: Can only take on a set number of values
• Example: classes missed last week, puppies in a litter
continuous: Can take on any value within some interval (most
of the time you need some sort of tool to measure a continuous
variable.)
• Examples: Height, weight, speed
Population any completecollection of people or objectsthat a statistician is interestedin
studying
Parameter value that
describes a characteristic of a
population
Sample the smaller group of cases from the population of interest that are used
to collect data.
- A sample must: representative, selected randomly, and large enough.
statistics the quantity calculated from the sample.
Sampling frame list of cases from which a sample is drawn;usually a large subset of the population
Simple random sample method of sampling in which everymember of the sampling frame has the same
chance of being chosen
Systematic sample method of sampling where members aresampled according to some
predetermined rule by skipping a certainnumber of people and then sampling the
nth person
Stratified sample The population is arranged in groups based on some
characteristic and a random sample is chosen from each group.
Cluster sample sampling method where the population is divided
into similar groups (called clusters), a simple random sample of the
clusters is taken, and then every member in each selected cluster
becomes part of the sample
Multi-Stage sample When two or more sampling techniques are used in stages.
Bad sampling methods convenience and voluntary
convenience sample a sample obtained from the people who
were easiest to access
C
Terms in this set (129)
Data collection the process and methodology of obtaining data from a
population or sample, including survey design, experiments, and observational
studies.
Descriptive statistics methods for organizing, summarizing, and presenting data
using numerical measures, tables, and graphical displays.
Probability the mathematical framework used to quantify uncertainty and
measure the likelihood of events in a random experiment.
Inferential statistics methods of using information from a sample to draw
conclusions about the population.
Cases the people or objects included in the study.
- Respondents, subjects, participants, experimental units
Variable the characteristic of the case to be measured or observed.
- Identifier variable
Categorical variable divides cases into groups, placing eachcase into exactly one or more categories.
It consists of groups orcategory names.• Examples: Eye color, political party,
educational level
two types of Categorical variable nominal: ordering of categories does not matter
• Example: Sex, phone brand
ordinal: ordering of categories does matter
• Examples: Final grade, clothing size
, Quantitative variable measures a numerical quantity for
each case. It consists of numerical measures or counts.
• Examples: Height, temperature, number of children per family
two kinds of quantitative variable discrete: Can only take on a set number of values
• Example: classes missed last week, puppies in a litter
continuous: Can take on any value within some interval (most
of the time you need some sort of tool to measure a continuous
variable.)
• Examples: Height, weight, speed
Population any completecollection of people or objectsthat a statistician is interestedin
studying
Parameter value that
describes a characteristic of a
population
Sample the smaller group of cases from the population of interest that are used
to collect data.
- A sample must: representative, selected randomly, and large enough.
statistics the quantity calculated from the sample.
Sampling frame list of cases from which a sample is drawn;usually a large subset of the population
Simple random sample method of sampling in which everymember of the sampling frame has the same
chance of being chosen
Systematic sample method of sampling where members aresampled according to some
predetermined rule by skipping a certainnumber of people and then sampling the
nth person
Stratified sample The population is arranged in groups based on some
characteristic and a random sample is chosen from each group.
Cluster sample sampling method where the population is divided
into similar groups (called clusters), a simple random sample of the
clusters is taken, and then every member in each selected cluster
becomes part of the sample
Multi-Stage sample When two or more sampling techniques are used in stages.
Bad sampling methods convenience and voluntary
convenience sample a sample obtained from the people who
were easiest to access
