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Stack #184727

QuestionAnswer
way to select a random sample from a directory or list that is much more efficient than simple random sampling systemic sampling
- approximate known and equal chance of selection - efficiency - less expensive advantages systemic sampling
is employed when the researcher realizes that respondents will need to apply different menatal effor to groups of questions work approach
placement of numbers on the questionnaire to facilitate data entry after the survey has been conducted precoding
more accurate overall sample of skewed population advantage of stratified
can serve as the basis for reliability and validity measures function of questionnaire
a subset of the population that should represent the entire group sample size
one the marketing manager can potential use as a basis for marketing decisions meaningful difference
any error that occurs in a survey because a sample is used sampling error
-two group comparison - probability difference - mean difference T-Test
categories are created before observation and provided on observation forms break down
the entire group under study as defined by reasearch objectives population
the basic level of investigation. Consumers, store, shelf facings, teens sample unit
an acccounting of the complete population census
- at the presence of breakfast, we have the presence of coffee - at the presence of lunch we have the absence of coffee non-monotonic
- complete accounting of population needed - cumbersome to provide unique designations to every population member Disadvantages Simple Random sampling
Fosters cooperation and motivation Functions of Questionnaire
Multigroup Comparison ANOVA
Standardizes those questions and the response categories Function of Questionnaire
Translates the reserach objectives into specific questions Function of Questionnaire
Can speed up the process of data analysis Function of Questionnaire
Serves as permanent records of the research Fuction of Questionnaire
Perform observations first then build categories Build-Up
A set of procedures in which the sample size and sample statistics are used to make estimates of popoulation parameters Statistical Inference
Hypotheses that indicate the direction in which you believe the population parameter falls relative to some target mean or percentage Differential Hypothesis
Instances in which the chances (probability of selecting members frmo the population into the sample are unknown Non-Probability Samples
the marketer can focus various marketing strategies and tactics, such as different ad appeals, different versions of the product, different prices, or different channels of distribution Actionable Differences
Method in which the population is divided into groups, any of which can be considered a representative sample Cluster Sampling
One that will be in place for the forseeable future Stable Differences
Organizes questions into sets based on a common objective of questions in the set Sections approach
"what we wish to know" about a population parameters
are used to ESTIMATE population parameters Statistic
The difference in the sample may be assumed to exist in the populations from which the random samples are drawn Statistical Significance difference
Assesses nonmonotonic associations in corss tab tables. Based upon differences between observed and expceted frequencies Chi-Square
small loss in sampling precision disadvantage systemic sampling
method in which the population is separated into different strata and a sample is taken from each stratum stratified sampling
the general direction of a relationship between two variables is know, KIDS and SHOES monotonic
- the known and equal chance of selection - easy method when there is an electronic database advantages simple random sampling
ones in which members of the population have a known chance (probability) of being selected into the sample probability sample
more complex sampling plan requiring different sample sizes for each stratum disadvantages stratified sampling
Economic Efficiency advantage cluster sampling
cluster specification errors, the more homogeneous the cluster the more precise the sample result disadvantage cluster sampling
some curved patern describes the associations. Job satisfaction high then low then high curvilinear
"straight-line" association between variables linear
consists of rows and columns defined by the categories classifying each of the two variables Cross-Tabs
the probability of being selected into the sample is "known" and equal for all members of the population Simple Random Sampling
used to generate conclusions about the populations characteristics based on the sample data inferential analysis
used to compare the means of the responses of one group to that of another group differences analysis
indicated the degree of variation in a way that can be translated into a bell shaped curve distribution standard deviation
values that are computed from information provided by a sample statistic
refers to how close a random samples statistic is to the true populations value it represents accuracy
creation of a computer file that hold the raw data taken from all of the questionnaires deemed suitable for analysis data entry
used to desribte the data set descriptive analysis
allows one to make forecasts for future events predictive analysis
a statistical procedure used to "accept" or reject" the hypothesis based on sample information hypothesis
determines the strength and direction of realtionships between two or more variables associative analysis
values that are computed from a complete census which are considered to be precise and valued measure of the population WANT TO KNOW MOST parameters
identification codes that pertain to the possible responses for each question on the questionnaire data coding
the degree to which the sample frame fails to account for all of the defined units of the population, a telephone book listing does not contain unlisted numbers sample frame error
a master list of the entire population sample frame
refers to how similar or dissimilar responses are to given questions variability
Created by: Ninna
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