Article interpretation with data verification

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Article: ___________________________________________________________________________ ___________________________________________________________________________ Interpretation with Data Verification: ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________ Assessment 3: Data Analysis Report Use these activities as a guide for the qualitative component of this assessment!
41 | P a g e WEEK 8 QUANTITATIVE DATA PREPARATION The value of marketing research is its ability to provide accurate decision-making information to the user. To accomplish this, the data must be converted into usable information or knowledge. After collecting data through the appropriate method, the task becomes one of ensuring the data provides meaning and value. Data preparation is the first part of the process of transforming data into useful knowledge. This process involves several steps: (1) data validation, (2) editing and coding, (3) data entry, (4) data tabulation. Data analysis follows data preparation and facilitates proper interpretation of the findings. Data preparation is essential in converting raw data into usable coded data for data analysis. It plays an important role in assessing and controlling data integrity and ensuring data quality by detecting potential response and nonresponse biases created by interviewer errors and/or respondent errors, as well as possible coding and data entry errors. Data preparation is important in dealing with inconsistent data from different sources or in converting data in multiple formats to a single format that can be analysed with statistical software. KEY TERMS AND CONCEPTS FROM WEEK 8 I. _____________________________________________________________________ _____________________________________________________________________ II. _____________________________________________________________________ _____________________________________________________________________ III. _____________________________________________________________________ _____________________________________________________________________ IV. _____________________________________________________________________ _____________________________________________________________________ V. _____________________________________________________________________ _____________________________________________________________________
42 | P a g e WORKSHOP 8 Activity 1: Data Coding Data Coding involves grouping and assigning values to various responses from the survey instrument. 1. Use the below questionnaire for Baskin Robbins to establish a Master Code on which the assigned numeric values are shown for reach response.
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44 | P a g e Thank you for your participation
45 | P a g e Activity 2: Transcribing (Data Entry) Perform Data Entry by: a. Setting up the variables in SPSS in Variable View, as coded in the previous activity. b. Enter the responses for each question from each of the ten questionnaires into SPSS in Data View. Activity 3: Data Tabulation (Data Entry Error Detection) Perform data tabulation on each of the variables to detect whether you have entered any incorrect values outside of the code ranges for each of the variables (see Appendix D, p. 113 for SPSS instructions).
46 | P a g e WEEK 9 UNIVARIATE ANALYSIS Once data have been collected and prepared for analysis, several statistical procedures can help to better understand the responses. It can be difficult to understand the entire set of responses because there are too many numbers to look at. Consequently, almost all data needs summary statistics to describe the information it contains. Basic statistics and descriptive analysis achieve this purpose. Frequency distributions can be useful for examining the different values for a variable.

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