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¡TOPIC 5: SAMPLING PLAN AND DATA COLLECTION

Sample or Census( differences: census is a complete enumeration of all the people and ask them what opinion they have, the problem is imposible to have all population… sampling is choosing people in order to know something about the population; know things about the population)

Sampling design process:1.Determine the Target Population2.Determine the Sampling Frame ( how I can identify them)3.Select a Sampling TechniqueSampling Techniques:

NON PROBABILITY SAMPLING TECHNIQUES–      Convenience Sampling–      Judgemental Sampling: –       Quota Sampling: The technique tries to use some framework to define-       Snowball Sampling.( use when the thing is very complex)   PROBABILITY SAMPLING TECHNIQUES–       Simple Random Sampling:All the elements havethesameprobabilityofselectiontoparticipateintheresearch.

–      Systematic Sampling:The first element of the sampleisselectedusingtherandomsampleapproachStratified Sampling:Two step process to partition the population in subsequent populations (or strata). The Strata are supposed to be homogeneous within them and heterogeneous between.–       Cluster Sampling:Two step process to create clusters. The groups should be mutually exclusive and collectively exhausted. Thegroupsarehomogeneousbetweenthembutheterogeneouswithin.Theidea is have several subgroups that can becompared–       Other Sampling Techniqeso   Sequential Sampling: We choose a small group and sample more if it is necessary to achieve certain statisticalcriteriao   Double Sampling: We choose a sample in order to do the researcher, and then select a subsample of the sample

Determine the Sample SizeSample Size:  Number of elements to be included in the research. Qualitative and Quantitative factor should be included in their calculation. /// the qualitative factors are: the importance of the decision, the nature of the research, the number of variables, the nature of the analysis, sample sizes used in similar studies, incidence rates (number of people who will answer the questionnaire) , completion rates, resource constraints

Execute the Sampling Process–      Decide how the decisions about the population, sampling unit, sampling frame, sampling technique and sample size are going to be implemented.-       This is necessary because the persons that design the research and the person that collect the data are not the same.-       In the majority of the research designs more than one person is involved.

Validate the Sample–       We need to search the sampling frame error ( VALIDATE THE POPULATION-        The usual process is doing filter questions like screening participants during the data collection.-       The screening can be applied with filter questions about:– Demographiccharacteristics–  Knowledge of theproduct–  Usage of theproduct

TOPIC 6: DATA PREPARATION

The Data Preparation Process Preliminary Plan of Data Analysis:What data we want to analyze. This was previously done when we defined our Research Approach–  What is the Marketing DecisionProblems–  What is the information needed in our Marketing ResearchProblem–  What are our objectives, hypothesis about the Research ProcessBased on these we have an idea of the type of information that we need, the nature of the information (Exploratory, Descriptive or Conclusive) andwhat answers we shouldobtain.

Editing:This is to correct in order to go more deep. It is the review of thequestionnaire for increasing accuracy and precession. It includes reviewing for answers that are: Illegible, Incomplete, Inconsistent, Ambiguous

The idea is try to make some type of arrangement to recover the data. Unsatisfactory Responses:

–  Return to the field: When respondents are easily identifiable and the sample size issmall

– AssigningMissingValues:Whentheproportionofthisquestionsissmall, the number of questionnaires is small and do not affect keyquestions

Coding:Take the questionnaire and decide which ones will be coding. Many questionnaire and data entry software nowadays are automatic. In any case a good coding method for the questions is suggested in order to make easy the interpretation. The basics imply assign a number to each possible question. The open ended questions should be included in other column(for example the option other) The idea is use simple numerical codes. This comes from the “ASCII” file tradition, that is a type of coding used for computer format that requires low memory to storage.  ////  Codebook:Is an Encyclopedia of our research, to interpretate the data analysis that explains the names of each questions and the possible number that answer each questions. Then, when we have our codes ///// Transcribing: Keying the coded data into computers. If we use CATI or CAPI this step is already done automatically when we are recording the interviews.//// Cleaning the Data:Thorough and extensive checks for consistency and treatment of missing responses.

Statistically Adjusting the Datao   Weighting: Accounting for non response giving different weight to the response based on the respondingrates.o   Variable Respecification: The transformation of variables or creation of new ones, so they are more consistent with the purpose of ourstudy.o   Scale Transformation: A manipulation of Scale values to ensure compatibility with other scales or otherwise make the data suitable for analysis (Ex.Standarization)  Select Data Analysis Strategy