82 terms

Exam 3

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Terms in this set (...)

Sampling
process of obtaining information from a subset of a larger group
population
entire group of people about whom information is needed; also called universe or population of interest.
census
collection of data obtained from or about every member of the population of interest
sample
subset of all the member of a population of interest
sampling frame
list of population elements from which units to be sampled can be selected or a specified procedure for generating such a list
random digit dialing
method of generating lists of telephone numbers at random
probability sample
samples in which every element of t he population has a known nonzero likelihood of selection
non probability sample
samples in which specific elements from the population have been selected in a nonrandom manner
sample size
the identified and selected population subset for the survey, chosen because it represents the entire group

n = (Z^2)(SD^2) / SE^2
population parameter
a value that accurately portrays or typifies a factor of a complete population, such as average age or income
sampling error
error that occurs because the sample selected is not perfectly representative of the population
non sampling error
all errors other than sampling error; also called measurement error
simple random sample
probability sample selected by assigning a number to every element of the population and then using a table of random numbers to select specific elements for inclusion in the sample
systematic sampling
probability sampling in which the entire population is numbered and elements are selected using a skip interval
stratified sample
probability sample that is forced to be more representative through simple random sampling of mutually exclusive and exhaustive subset
proportional allocation
sampling in which the number of elements selected from a stratum is directly proportional to the size of the stratum relative to the size of the populations
disproportional (optimal) allocation
sampling in which the number of elements taken from a given stratum is proportional to the relative size of the stratum and the standard deviation of the characteristic under consideration.
cluster sample
probability sample in which the sampling units are selected from a number of small geographic areas to reduce data collection costs
multistage area sampling (multistage area probability sampling)
geographic areas selected for national or regional surveys in progressively smaller population units, such as counties, then residential blocks, then homes
convenience samples
non probability samples based on using people who are easily accessible
judgment sample
non probability sample in which the selection criteria are based on the researcher's judgment about representativeness of the population under study.
quota samples
non probability samples in which quotas, based on demographic or classification factors selected by the researcher, are established for population subgroups
snowball samples
non probability samples in which additional respondents are selected based on referrals from initial respondents
central limit theorem
idea that a distribution of a large number of sample means or sample proportions will approximate a normal distribution, regardless of the distribution of the population from which they were drawn
normal distribution
continuous distribution that is bell shaped and symmetric about the mean; the mean, median, and mode are equal.
proportional property of the normal distribution
feature that the number of observations falling between the mean and a given number of standard deviations from the means is the same for all normal distribution
standard normal distribution
normal distribution with a mean of zero and a standard deviation of one
standard deviation
measures of dispersion calculated by subtracting the mean of the series from each value in series, squaring each result, summing the results, dividing the sum by the number of items minus 1, and taking the square root of this value.
population distribution
frequency distribution of all the elements of a population
sample distribution
frequency distribution of all the elements of an individual sample
sampling distribution of the mean
theoretical frequency distribution of the means of all possible samples of a given size drawn from a particular population; it is normally distributed.
standard error of the mean
standard deviation of a distribution of sample means

SD/Sqroot(n)
point estimate
particular estimate of a population value
interval estimate
interval or range of values within which the true population value is estimated to fall
confidence level
probability that a particular interval will include true population value; also called confidence coefficient
confidence interval
interval that, at the specified confidence level, includes the true population value
sampling distribution of the proportion
relative frequency distribution of the sample proportions of many random samples of a given size drawn from a particular population; it is normally distributed
allowable sampling error
amount of sampling error the researcher is willing to accept
population standard deviation
standard deviation of a variable for the entire population
independence assumption
assumption that sample elements are drawn independently
finite population correction factor
an adjustment to the required sample size that is made in cases where the sample is expected to be equal to 5 percent or more of the total population
statistical power
probability of not making a type 2 error
validation
process of ascertaining that interviews actually were conducted as specified.
editing
process of ascertaining that questionnaires were filled out properly and completely
skip pattern
sequence in which later questions are asked based on a respondent's answer to an earlier question or questions.
coding
process of grouping and assigning numeric codes to the various responses to a question
data
process of converting information to an electronic format.
intelligent data
form of data in which the information being entered into the data entry device is checked for internal logic.
scanning technology
form of data entry in which responses on questionnaires are read in automatically by the data entry device
logical or machine cleaning of data
final computerized error check of data
error checking routines
computer programs that accept instructions from the user to check for logical errors in the data
one way frequency table
tables showing the number of respondents choosing each answer to a survey question
cross tabulations
examination of the responses to one question relative to the responses to one or more other questions
mean
sum of the values for all observations of a variable divided by the number of observations.
median
value below which 50 percent of the observations fall
mode
values that occurs most frequently
statistically significant
a difference that is large enough that it is not likely to have occurred because of chance or sampling error.
hypothesis
assumption or theory that a researcher or manager makes about some characteristics of the population under study.
null hypothesis
the hypothesis of status quo, no difference, no effect
decision rule
rule or standard used to determine whether to reject or fail to reject the null hypothesis
type 1 error
rejection of the null hypothesis when, in fact, it is true (a error)
type 2 error
failure to reject the null hypothesis when, in fact, it is false (B error)
p value
exact probability of getting a computed test statistic that is due to chance. the smaller the P value, the smaller the probability that the observed result occurred by chance.
correlation analysis
analysis of the degree to which changes in one variable are associated with changes in another.
pearson's product moment correlation
a correlation analysis technique for use with metric data
regression analysis
a procedure for predicting the level or magnitude of a (metric) dependent variable based on the level of multiple independent variables.
coefficient of determination
a measure of the percentage of the variation in the dependent variable explained by variations in the independent variables.
regression coefficient
estimates of the effect of individual independent variables on the dependent variable
dummy variables
in regression analysis, a way of representing two - group or dichotomous, nominally scaled independent variables by coding one group as 0 and the other as 1.
collinearity
the correlation of independent variables with each other, which can bias estimates of regression coefficient.
causation
inference that a change in one variable is responsible for (caused) an observed change in another variable
scaling of coefficients
a method of directly comparing the magnitudes of the regression coefficients of independent variables by scaling them in the same units or by standardizing the data.
cluster analysis
a general term for statistical procedures that classify objects or people into some number of mutually exclusive and exhaustive groups on the basis of two or more classification variables
factor analysis
a procedure for simplifying data by reducing a large set of variables to a smaller set of factors or composite variables by identifying underlying dimensions of the data
factor
a linear combination of variables that are correlated with each other
factor loadings
correlation between factor scores and the original variables
conjoint analysis
a procedure used to quantify the value t hat consumers associated with different levels of product/service attributes or features.
utilities
the relative value of attribute levels determined through conjoint analysis
executive summary
portion of a research report that explains why the research was done what was found, what those findings mean and what action, if any, management should undertake
conclusions
generalizations that answer the questions raised by the research objectives or other wise satisfy the objectives
recommendations
conclusions applied to marketing strategies or tactics that focus on a client's achievement of differential advantage.
research management
overseeing the development of excellent communication systems, data quality, time schedules, cost controls, client profitability, and staff development