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Indicator 3.05. Interpret marketing information to test hypotheses and/or to resolve issues. Need for physical inspection of paper-based marketing data. If errors are caught early, they can be corrected. Standardizations and continuity
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Indicator 3.05 Interpret marketing information to test hypotheses and/or to resolve issues.
Need for physical inspection of paper-based marketing data • If errors are caught early, they can be corrected. • Standardizations and continuity • Missing values/nonuniform data entry which means changing the value or formula of the response codes.
Actions that can be taken with incomplete records • Cleanse the data which includes dropping problematic data.
Reasons for data entry errors that limit the use of marketing research data • Wrong entry • Failure of data entry technology
Reasons that questionable entries are found in raw marketing research data • Honesty
Role of coding in processing marketing data • Procedure converts the edited raw data into numbers or symbols • Code book is created
Paper-based marketing information vs. computer-based marketing information • Computer based software saves time and money. • The programs have error checking built in to prevent common errors. • The availability of the item bank makes it easier to build questionnaires.
Importance of using a codebook to describe data and to indicate where and how they can be accessed • Shows each question in the questionnaire • Shows the variable nameand label • Shows the variable type, values and value lables.
Vocabulary • Descriptive statistics • Mean • Medium • Mode • Range • Standard deviation • skewed
Objectives of using descriptive statistics to interpret data • To summarize a data set rather than use the data to learn about the population that the data are thought to represent. • Provides simple summaries about the sample and the measures. • Summarizes data
Advantages and disadvantages of using the mean, median, and mode as measures of central tendency • A disadvantage of the median is the difficulty of handling it.
When to use the mean, median, and mode • Mean - range/intervals/ratio • Median – Ranking/Ordinal Scale • Mode – Response question/nominal
Importance of using the median when working with skewed distributions • The median can be used as a measure of location when a distribution is skewed, when end-values are not known, or when one requires reduced importance to be attached because of measurement errors.