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88 Cards in this Set

  • Front
  • Back

An art and a science: Collection, organization, summarization, presentation and to draw Conclusions.


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

Descriptive Statistics

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

Inferential Statistics

A characteristic or attribute that can assume different values


A variable whose values are determined by chance

Random Variable

measurements or observations for a variable


the totality of all subjects possessing certain common characteristics that are being studied


a group of subjects selected from the population


a characteristic or measure obtained by using all the data values for a specific population


the science of conducting studies to collect, organize, summarize, analyze, and draw conclusions from data


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

Qualitative Variable

a variable that is numerical in nature and that can be ordered or ranked

Quantitative Variable

A variable that assumes values that be counted

discrete variable

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

continuous variable

a measurement level that classifies data into mutually exclusive exhaustive categories in which no order or ranking can be imposed on them

Nominal level of measurement

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

Ordinal level of measurement

a measurement level that ranks data and in which precise differences between units of measure exist

Interval level of measurement

a measurement level that passes all the characteristics of interval measurement and a true zero: it also has true ratios between different unit of measure

ratio level of measurement

a sample obtained by numbering each element in the population, and then selecting every K'th number from the population to be included in the sample

systematic sampling

a sample obtained by dividing into sub groups called strata, according to various homogenous characteristics and then selecting members from each stratum

stratified sampling

a sample obtained by selected a preexisting or natural group called a cluster, and using the members in the cluster for the sample

cluster sampling


population count sample every 10 years

a study in which the researcher merely observes what is happening, or what has happened in the past and draws conclusions based on these observation

observational studies

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

experimental studies

A collection of data value forms a

Data set

each value in the data set is called a

data value or datum

data can be used in these two different ways

Discriptive and Inferential Statistics

example of discrpitive statistic is


What type of statistic uses probability?

Inferential Statistic

decision making process for evaluating claims about a population based on information obtained from samples. Give an example.

hypothesis testing, example releasing a new prescription drug

statisticans use these to determine relationship among variables. give an example.

inferential statistics example: surgeon general warning of 1964, a car dealer knows what to order on what month and how many of each.

example: subjects are classified according to gender other example are religious preference and geographical locations

Qualitative Variable

for example the variable age is numerical, and people can be ranked in order according to the value of their ages. another example is heights, weights, and body temperatures.

Quantitative variable

Quantatative variables can be further classified into two groups

discrete and continuous variables.

example of a discete variable

number of children in the family, and number of students in the class room, and a number of class received by switch board operator for each day of the month.

an example of continuous variable


measurement scales

how variable are categorized, counted or measured uses

the four common types of measurement scales

nominal, ordinal, interval, and ratio

a sample of college instructor classified according to subject taught, english, history,pyschology, or mathematics is an example of and classifying survey subject as male or female.

nominal level

when people are classified according to their built (small medium large) or first place second place 3rd place at a competition or position at work are all examples of

ordinal level

measurments of height weight area and number of phone call received are examples of

ratio level

to obtain samples that are unbaised statisticians use four basic methods of sampling called

random, systematic, stratified, and cluster sampling

a researcher interviewing subjects entering a local mall to determine what are they buying what store they are going to. this interview accord during a specific time meaning that people who walked in before didnt participate is an example of

convenience sample

an experimental study is the one that is being manipulated by the researcher; the result in variable is called

independent variable also called the explanatory variable; dependent variable and outcome variable

the disadvantage with the experiamental study is called

hawthorne effect

a variable that is the one that influences the dependent or outcome variable but what was not seprated from the independent variable is called

confounding variable

A survey to collect data on the entire population is

a census

in a questionary, respondents are asked to mark their gender as male or female , gender is an example of the

nominal level of measurement

the nominal scale of measurement has the properties of

A)Ordinal Scale

B)only interval scale

C)ratio scale

D) none of these alternatives are correct


the scale of measurement that is used to rank order , the observation for the variable is called the

Ordinal Scale

rating of excellent, great, poor , very poor is an example of what scale

ordinal scale

the ordinal scale of measurement has the properties of the

nominal scale

the ratio scale of measurement has the properties of the

interval scale

temparature is an example of a variable that uses the

interval scale

the interval scale of measurement has the properties of

A) ratio and nominal scale

B)ratio and ordinal scale

C) ratio scale

D) none of these alternatives are correct


Income is an example of a variable that uses the

ratio scale

arithmetic operations are appropriate for

A)only the ratio scale

B)only the interval scale

C) nominal scale

D) none of these


quantitative data refers to data obtained with the

interval or ratio scales

the entities on which data are collected are


the set of measurements collected for a particular element are called


a characteristic of interest for the element is called a


all the data collected in a particular study are refered to as the

data set

another name for observations


quantitative data are

always numeric

The number of cases will always be the same as the number of


qualitative data can be

maybe either numeric or non numeric

ordinary arithmetic operations are meaningful


temperature is an example of a

quantitative variable

For ease of data entry into a university database, 1 denotes that the student is a undergraduate and 2 indicated that the student is a graduate student... in this case data are

Qualitative varibale

arithmetic operations are inappropriate for

qualitative data

income is an example of

quantitative data

data collected at the same or approximately the same point in time are

cross sectional data

data collected over several time periods are called

time series data

statistical studies in which researchers do not control variable of interest

observational studies

statistical studies in which researchers control variables of interest

experimental studies

the summaries of data, which may be tabular, graphical, or numerical are refered to as

descriptive statistics

the process of drawing inferences about the population based on the information taken from the sample

statistical inference

the collection of all elements of interest in a particular study


in a sample of 800 students in a university , 240 or 30%, are business majors .... the 30% is an example of

descriptive statistics

in a sample of 400 students in a university , 80 or 20% are business majors... based on the above information, the schools paper reported that 20% of all the students at the university are business majors. this report is an example of

Statistical inference

500 residents of a city are pulled to obtain information on voting intentions in a upcoming city election. the 500 residents are an example of a


a statistics professor asks students in call their age .. on the basis of this information the professor states that the average age of students in the university is 24 years ... this is an example of

statistical inference

the owner of a factory regularly requests a graphical summary of all employee salaries .. the graphical summary of salaries is an example of

descriptive statistic

the department of transportation of a city has noted that on the average there are 17 accidents per day , the average number of accidents is an example of

descriptive statistic

the process of analyzing sample data in order to draw conclusions about the characteristics of a population is called

statistical inference

in a post office the mail boxes are numbered from 1-4500 these numbers represent


the average age in a sample of 190 students at city college is 22 .. as a result of the sample it can be concluded that the average age of all students at city college ...

could be larger smaller or equal to 22

since the sample is the sub set of the population .. the sample mean ...

could be larger smaller or equal to the population