Chapter 1 - Stat 1

Experimental Study

A study in which the researcher manipulates one of the variables and tries to determine how the manipulation influences other variables.

Observational Study

A study in which the researcher merely observes what is happening or what has happened in the past and draws conclusions based on these observations.

Quasi-Experimental Study

A study that uses in tact groups rather than random assignment of subjects to groups.

Measurement Scales

A type of classification that tells how variables are categorized, counted, or measured; the four types of scales are: - nominal (color) - ordinal (1st, 2nd, 3rd) - interval (Temperature) - ratio (mph, measurement)

Data Value or Datum

A value in a data set.

Independent Variable

A variable in correlation and regression analysis that can be controlled or manipulated.

Dependent Variable

A variable in correlation and regression analysis that cannot be controlled or manipulated.

Discrete Variable

A variable that assumes values that can be counted.

Continuous Variables

A variable that can assume all values between any two specific values; a variable obtained by measuring.

Qualitative Variables

A variable that can be placed into distinct categories, according to some characteristic or attribute.

Confounding Variable

A variable that influences the outcome variable by cannot be separated from the other variables.

Explanatory Variable

A variable that is being manipulated by the researcher to see if it affects the outcome variable.

Quantitative Variable

A variable that is numerical in nature and that can be measure or counted.

Outcome Variable

A variable that is studied to see if it has changed significantly due to the manipulation of the explanatory variable.

Random Variable

A variable whose values are determine by chance.

Probability

The chance of an event occuring

Sampling Error

The difference between the sample measure and the corresponding population measure due to the fact that the sample is not a perfect representation of the population.

Population

To totality of all subjects possessing certain common characteristics

Retrospective Study

A study in which data are collected from records obtain from the past.

Cross-Sectional Study

A study in which date are collected at one point in time.

Example of Inferential Statistics

- Because of the current economy, 49% of 18 to 34 year olds have taken a job to pay the bills. - In 2011, 79% of U.S. adults used the Internet. - Forty-four percent of the people in the United States have type O blood.

Example of Differential Statistics

- Because of the current economy, 49% of 18 to 34 yearolds have taken a job to pay the bills. - In an online survey of 500 Virginia Tech students between spring 2010 and spring 2011, 31% said that they had missed class because of alcohol consumption. - In 2008-2009, a total of 260,327 U.S. students were studying abroad.

Inferential Statistics

A branch of statistics that consists of generalizing from samples to populations, performing hypothesis testing, determining relationships among variables, and making predictions.

Descriptive Statistics

A branch of statistics that consists of the collection, organization, summarization, and presentation of data.

Variable

A characteristic or attribute that can assume different values.

Statistics

A characteristics or measure obtained by using the data value from a sample.

Boundary

A class of numbers in which a date value would be placed before the data value has been rounded.

Data Set

A collection of data values.

What is a confounding variable?

A confounding variable is one that can influence the results of the research study when no precautions were taken to eliminate it from the study.

Hypothesis Testing

A decision-making process for evaluating claims about a population.

Explain the difference between discrete and continuous variables.

A discrete variable is a variable that is finite and can be counted, like an apple or a child. In the other hand, a continuous variable is nonfinite, it can be forever small or large.

Systematic Sample

A distribution in which the data values are uniformly distributed about the mean.

Treatment Group

A group in an experimental study that has received some type of treatment.

Control Group

A group in an experimental study that is not given any special treatment.

Sample

A group of subjects selected from the population.

Ordinal Level of Measurement

A measurement level that classifies data into categories that can be ranked; however, precise differences between the ranks do not exist.

Nominal Level of Measurement

A measurement level that classifies data into mutually exclusive (nonoverlapping) exhaustive categories in which no order or ranking can be imposed on them.

Ratio Level of Measurement

A measurement level that possesses all the characteristics of interval measurement and a true zero; it also has true ratios between different units of measure.

Interval Level of Measurement

A measurement level that ranks data and in which precise differences between units of measure exits. Example: - GPA - Temperature

Stratified Sample

A sample obtained by diving the population into subgroups, called strata, according to various homogeneous characteristics and the selecting members from each stratum.

Cluster Sample

A sample obtained by selecting a pre existing or natural group, called a cluster, and using the members in the cluster for the sample.

Random Sample

A sample obtained by using random or chance methods; a sample for which every member of the population has an equal change of being selected.

Matched-Pair Design

A statistical study where subjects are matched and then one subject is assigned to a treatment group and the other subject is assigned to a control group.

Completely Randomized Design

A statistical study where the subjects are assigned to groups by randomization and treatment are assigned to groups by randomization.

Longitudinal Study

A study conducted over a period of time.

Census

Accounting (usually done by government) of all member of the population.

Hawthorne Effect

An effect on an outcome variable that has two outcomes when sampling is done without replacement.

Nonsampling Error

An error that occurs erroneously or from a biased sample.

Why are continuous variables rounded when they are used in statistical studies?

Continuous variables need to be rounded because of the limits of the measuring device.

What is meant by blinding and double-blinding?

Blinding is used to help eliminate the placebo effect. Here the subjects are given a sugar pill that looks like the realmedical pill. The subjects do not know which pill they are getting. When double blinding occurs, neither the subjects nor the researchers are told who gets the real treatment or the placebo.

What are five ways data can be collected?

Data can be collected by using telephone surveys, mail questionnaire surveys, personal interview surveys, by taking a look at records, or by direct observation methods.

List some advantages and disadvantages of an observational study.

One advantage of an observational study is that it can occur in a natural setting. In addition, researchers can look at past instances of statistics and draw conclusions from these situations. Another advantage is that the researcher can use variables, such as drugs, that he or she cannot manipulate. One disadvantage is that since the variable cannot be manipulated, a definite cause-and-effect situation cannot be shown. Another disadvantage is that these studies can be expensive and time-consuming. These studies can also be influenced by confounding variables. Finally, in these studies, the researcher sometimes needs to rely on data collected by others.

Explain the difference between descriptive and inferential statistics.

Descriptive statistics consists of the collection, organization, summarization, and presentation of data while inferential statistics consists of generalizing from samples to populations, performing estimations and hypothesis testing, determining relationships among variables, and making predictions.

Blocks

Groups of a subjects with similar characteristics in a statistical study that receives different treatments when these characteristics might make a difference in the outcome of the experiments.

What is the difference between a completely randomized design and a matched-pair design?

In a completely randomized design, the subjects are assigned to the groups randomly, whereas in a matched-pair design, subjects are matched on some variable. Then one subject is randomly assigned to one group, and the other subject is assigned to the other group. In both types of studies, the treatments can be randomly assigned to the groups.

What is the difference between an experimental study and a quasi-experimental study?

In an experimental study, the researcher has control of the assignment of subjects to the groups, whereas in a quasi-experimental study, the researcher uses intact groups.

Explain the difference between an observational and an experimental study.

In an observational study, the researcher observes what is happening and tries to draw conclusions based on the observations. In an experimental study, the researcher manipulates one of the variables and tries to determine how this influences the variables.

Why are a treatment group and a control group used in a statistical study?

In research studies, a treatment group subject receives a specific treatment and those in the control group do not receive a treatment or are given a placebo.

Data

Measurements or observations for a variable.

NOIR

Nominal, Ordinal, Interval, Ratio

Explain the difference between qualitative variables and quantitative variables.

Qualitative variables are variables that can be placed in distinct categories according to some characteristic or attribute and cannot be ranked, while quantitative variables are numerical in nature and can be ordered or counted.

Why are random numbers used in sampling, and how are random numbers generated?

Random numbers are used in sampling so that every subject in the population has an equal chance of being selected for a sample. Random numbers can be generated by computers or calculators; however, there are other ways of generating random numbers such as using a random number table or rolling dice.

Replication

Repetition of the study using different subjects.

Placebo Effect

Results of a study obtained by subjects who improve but not due to the conditions of the study.

Convenience Sample

Sample of subjects used because they are convenient an available

Why is information obtained from samples used more often than information obtained from populations?

Samples are used more than populations both because populations are usually large and because researchers are unable to use every subject in the population.

Blinding

Subject of the study do not know whether they are receiving a treatment or a placebo.

Volunteer Sample

Subject who decide for themselves to participate in a statistical study.

Double Blinding

Technique whereby subjects and researchers do not know whether the subjects are receiving a treatment or a placebo.