Module 1: Textbook Flashcards
A sample is used in statistical decision-making to represent a
population
In statistics, a sample is represented by data derived from —- (5)
observations, outcomes, responses, measurements or counts.
A parameter is a (numerical) description of a measurable ——-. A parameter provides information about ——
- population characteristic
- an entire population
A statistic is a (numerical) description of a —-. A statistic provides information about a ——-.
- sample characteristic
- portion, or subset, of a population
If another sample was selected from the population, the statistic in question most likely will have ——, since ——-.
- a different value than before
- no two samples are likely to be exactly the same
Example of a parameter
A social worker would like to know the average income of residents of a low-income apartment project and conducts a census by going door-to-door to obtain data. The population is residents of the project and the income data is a parameter since it represents the entire population.
Example of a statistic
A school nurse selected 40 sixth-grade students at random from the school class list and measured their height to obtain an estimate of the average height of all sixth graders at the school. The average she calculated was a statistic since it provided information from a sample representing the population of sixth graders at the school.
Descriptive statistics help us
to simplify the resulting large amounts of data in a way that makes the data easier to grasp (for sample)
Ex of descriptive statistics
Consider many students’ least favorite statistic, the Grade Point Average (GPA). GPA can be used to summarize and describe a student’s performance across a large number of classes.
Inferential statistics are used to make —- about things we cannot directly measure, while descriptive statistics are used to —– that we have somehow collected.
- generalizations
- describe a set of data
Descriptive statistics example:
Apartment
The researcher who collected data about the average income of residents of an apartment project published her information in a professional journal that reported a summary of the data. This is an example of descriptive statistics since it involved the organization, summarization, and display of the data.
Inferential statistics example:
Height
The school nurse who collected data on heights of sixth-graders used the data to make an estimate of the average height of all sixth grade students at the school. This is another example of inferential statistics, using data from a sample to reach a conclusion about the larger population of students.
Quantitative data can either be presented as
The numbers can be either continuous or discrete.
Qualitative data are presented as names or categories. They can be —, but not —-. The data are descriptive only, and cannot be operated on —–.
- observed
- measured
- mathematically
Nominal data
categories+numbers?
They can only be used as categories based on names, labels or qualities. The categories are mutually exclusive, meaning all cases must be sorted into one or another category with no overlap. Numbers may be used as labels but have no additional meaning or operability.
Examples of Nominal data
A list of postal codes represents nominal data. The codes may be shown as numbers or combinations of letters and numbers but have no mathematical properties; they only serve as identifiers.
Nominal data are — only
qualitative
Ordinal data (4)
can be either…+sorted+distance between data+ordering
- can be either quantitative or qualitative
- can be ordered, or ranked, with cases sorted into discrete groups.
- The distance between the data points is not meaningful
- The ordering can indicate higher, or lower, or more, or less with respect to some value or characteristic.
Ordinal data example
Finishing position in a marathon race is an example of ordinal data.
Interval data are —
quantitative
Interval data (4)
Distance between data+zero+math+ratios
- The distance between the data points is meaningful
- A zero simply represents a point on the scale and is not an inherent zero
- Since the distance between points is meaningful, values can be added and subtracted and averages can be calculated
- Ratios cant be calculated, due to lack of an inherent, or absolute, zero point.
Ratio data (4)
Interval+Zero+expressed+math
- Ratio data have meaningful intervals
- Have an inherent zero point.
- Since there is an inherent zero, the ratio of two data points can be meaningfully expressed as a multiple of another data point.
- Ratio level variables can be meaningfully added, subtracted, multiplied, and divided (ratios) and can be operated on to determine a variety of statistical measures.
Explain to me inherent zeros and ratio relationship
An inherent zero represents the total absence of something. In order to calculate ratios, the data set must have an inherent, or absolute, zero.
Example of Ratio data
Height and weight are examples of ratio data; they have absolute zero points.
Levels are usually — in nature.
categorical
Data are values obtained by ——. In social science research, they often are —– measures of some kind.
measuring or counting something
performance
Data vs level example
If an experiment were being conducted to compare four diets, then the variable diet would be considered to have four levels. The amount of weight loss while dieting can be measured, so is data.
Steps in designing a study: (6)
Experimental studies is designed to support claims of
cause and effect
A hallmark of the experimental study is —— of the treatment condition.
active manipulation
observational study (5)
What is it+ they do …. without+ subject/variable+treatment+ex
- An observational study is a study where researchers simply collect data based on what is seen and heard and infer based on the data collected.
- The researcher observes and measures differences between individuals or groups without influencing or manipulating any part of the environment.
- Researchers should not interfere with the subjects or variables in any way.
- The treatment that each subject receives may be a pre-existing condition that is determined beyond the control of the investigator.
- Jane Goodall’s work with chimpanzees in the wild may be the best-known example of a series of observational studies conducted in a natural environment.
Observational data has —-of conditions.
passive manipulation
Simulation (2)
What it is+ how its done
- involves modeling random events in such a way that the simulated outcomes closely match real-world outcomes.
- The simulation may be role-played to reproduce, as accurately as possible, the conditions of a real-life situation. In some cases, the researcher may use a mathematical or physical model, often a computerized program, to reproduce the conditions of a situation.
Survey
The researcher investigates characteristics of a population by having participants respond to questions, usually by interview, telephone, or mail.
A survey can be distinguished from an observational study in that a survey ——while ——
- requires an interaction with the participant(s)
- a true observational study does not
A controlled variable
a potentially confounding variable that has been ruled out as a possible influence on the results
The chief difference between experimental and non-experimental studies is in the way …..
the independent variable is identified and managed. In an experiment, the independent variable is actively manipulated by the researcher. In a non-experimental study, the independent variable usually has levels that are compared, but they are not actively manipulated.
A well-designed study will be both
valid and reliable
Replication of results involves
repeating an experiment with other participants to confirm that the same results can be obtained in another setting.
