CHAPTER 4 – KEY SENTENCES (SLIDES 3 E PÁGINA 145)
•
Secondary data are data originally collected for other purposes and can be obtained quickly
and are relatively inexpensive.
•
However, they have limitations and should be carefully evaluated to determine their
appropriateness for the problem at hand.
•
External data are generated by sources outside the organization and may be classified as
business/nongovernment, government, and syndicated services.
•
Business/nongovernment sources of secondary data include guides, directories, indexes, and
statistical data.
•
Government sources may be broadly categorized as census data and other data.
•
Syndicated services or sources are companies that collect and sell common pools of data
designed to serve several clients.
•
Big data denote any voluminous amount of structured, semi structured, and unstructured data
that have the potential to be mined for information.
•
Social media are sources of both internal and external secondary data and can be used to
collect primary data.
•
Mobile marketing research (MMR) can be employed for accessing secondary data and
providing survey-based syndicated services.
•
Ethical dilemmas that can arise include the unnecessary collection of primary data, the use of
only secondary data when primary data are needed, the use of secondary data that are not
applicable, and the use of secondary data that have been gathered through morally
questionable means.
CHAPTER 5 – KEY SENTENCES (SLIDES 4 E PÁGINA 184)
•
Qualitative and quantitative research should be viewed as complementary.
•
Qualitative research methods may be direct or indirect.
•
In direct methods, respondents can discern the true purpose of the research, while indirect
methods disguise the purpose of the research.
•
The major direct methods are focus groups and depth interviews.
•
Focus group interviews are the most widely used qualitative research technique.
•
Projective techniques are particularly useful when respondents are unwilling or unable to
provide the required information by direct methods.
•
Qualitative research can reveal the salient differences between the domestic and foreign
markets.
•
Whether focus groups or depth interviews should be conducted and how the findings should
be interpreted depends heavily on the cultural differences.
•
Social media constitute a rich domain to conduct qualitative research where the techniques
can be easily implemented.
•
Mobile marketing research can be appropriate for focus groups, depth interviews, and many
of the projective techniques.
CHAPTER 6 – KEY SENTENCES (SLIDES 5 E PÁGINA 229)
•
The two basic means of obtaining primary quantitative data in descriptive research are survey
and observation.
•
Each method has some general advantages and disadvantages.
•
The various methods may be compared in terms of task, situational, and respondent factors.
•
Although these data collection methods are usually thought of as distinct and competitive, they
should not be considered mutually exclusive.
•
The major methods are personal observation,
•
mechanical observation, audit, content analysis, and trace analysis.
•
As compared to surveys, the relative advantages of observational methods are (1) they permit
measurement of actual behavior, (2) there is no reporting bias, and (3) there is less potential
for interviewer bias.
•
Certain types of data can be obtained best, or only, by observation.
•
The relative disadvantages of observation are (1) very little can be inferred about motives,
beliefs, attitudes, and preferences; (2) there is the potential for observer bias; (3) most
methods are time-consuming and expensive; (4) it is difficult to observe some forms of
behavior; and (5) there is the potential for being unethical.
•
Observation is rarely used as the sole method of obtaining primary data, but it can be usefully
employed in conjunction with survey methodology.
•
In collecting data from different countries, it is desirable to use survey methods with equivalent
levels of reliability rather than the same method.
•
Social media can be employed to enhance traditional survey and observation research.
•
Mobile devices are also making inroads into ethnography, mystery shopping, and other forms
of observation.
•
People should not be observed without their consent for research in situations where they
would not expect to be observed by the public.
CHAPTER 7 – KEY SENTENCES (SLIDES 6 E PAGINA 260/261)
•
The scientific notion of causality implies that we can never prove that X causes Y. At best, we
can only infer that X is one of the causes of Y in that it makes the occurrence of Y probable.
•
Three conditions must be satisfied before causal inferences can be made: (1) concomitant
variation, which implies that X and Y must vary together in a hypothesized way; (2) time order
of occurrence of variables, which implies that X must precede Y; and (3) elimination of other
possible causal factors, which implies that competing explanations must be ruled out.
•
Experiments provide the most convincing evidence of all three conditions.
•
An experiment is formed when one or more independent variables are manipulated or
controlled by the researcher, and their effect on one or more dependent variables is measured.
•
In designing an experiment, it is important to consider internal and external validity.
•
Internal validity refers to whether the manipulation of the independent variables actually
caused the effects on the dependent variables.
•
External The internal and external validity of field experiments conducted overseas is generally
lower than in the United States.
•
The level of development in many countries is lower, and the researcher lacks control over
many of the marketing variables.
•
Using social media, such as virtual reality, the researcher can create an environment that
represents the field (marketplace) and yet exercise the degree of control possible
validity refers to the generalizability of experimental results.
•
There are four ways of controlling extraneous variables: randomization, matching, statistical
control, and design control.
•
Causal designs encompassing experimentation are most appropriate for inferring cause-andeffect relationships.
•
Although experiments have limitations in terms of time, cost, and administration, they are
becoming increasingly popular in marketing.
•
Test marketing is an important application of experimental design.
•
only in a laboratory setting.
CHAPTER 8 – KEY SENTENCES (SLIDES 7 E PAGINA 283)
•
Measurement is the assignment of numbers or other symbols to characteristics of objects
according to set rules.
•
Scaling involves the generation of a continuum upon which measured objects are located.
•
The fundamental scale characteristics are description, order, distance, and origin.
•
Finally, a scale that has origin also has distance, order, and description.
•
The four primary scales of measurement are nominal, ordinal, interval, and ratio.
•
In the ordinal scale, the next-higher-level scale, the numbers indicate the relative position of
the objects but not the magnitude of difference between them.
•
The interval scale permits a comparison of the differencesbetween the objects.
•
However, as it has an arbitrary zero point, it is not meaningful to calculate ratios of scale values
on an interval scale.
•
The highest level of measurement is represented by the ratio scale in which the zero point is
fixed.
•
The researcher can compute ratios of scale values using this scale.
•
The ratio scale incorporates all the properties of the lower-level scales.
•
Scaling techniques can be classified as comparative or noncomparative.
•
Comparative scaling involves a direct comparison of stimulus objects.
•
Respondents in many developed countries, due to higher education and consumer
sophistication levels, are quite used to providing responses on interval and ratio scales.
CHAPTER 14 – KEY SENTENCES DATA PREPARATION 460
•
Data preparation begins with a preliminary check of all questionnaires for completeness and
interviewing quality.
•
Editing consists oF screening questionnaires to identify illegible, incomplete, inconsistent, or
ambiguous responses.
•
Such responses may be handled by returning questionnaires to the field, assigning missing
values, or discarding the unsatisfactory respondents.
•
It is often helpful to prepare a codebook containing the coding instructions and the necessary
information about the variables in the data set.
•
Cleaning the data requires consistency checks and treatment of missing responses.
•
Statistical adjustments such as weighting, variable respecification, and scale transformations
often enhance the quality of data analysis.
•
The
selection of a data analysis strategy should be based on the earlier steps of the
marketing research process, known characteristics of the data, properties of statistical
techniques, and the background and philosophy of the researcher.
•
Before analyzing the data in international marketing research, the researcher should ensure
that the units of measurement are comparable across countries or cultural units.
•
The data analysis could be conducted at three levels: (1) individual, (2) within country or
cultural unit (intracultural analysis), and (3) across countries or cultural units (pancultural or
cross-cultural analysis).
•
When preparing and analyzing social media data, there are certain unique aspects involving
data collection, text coding and categorization, and text mining and visualization.
•
Data preparation and analysis in mobile marketing research is similar to that in online (Internet)
surveys.
•
Several ethical issues are related to data processing, particularly the discarding of
unsatisfactory responses, violation of the assumptions underlying the data analysis
techniques, and the evaluation and interpretation of results.
CHAPTER 15 – KEY SENTENCES CROSS TABS E MERDAS 503
•
Basic data analysis provides valuable insights and guides the rest of the data analysis as well
as the interpretation of the results.
•
A frequency distribution should be obtained for each variable in the data.
•
This analysis produces a table of frequency counts, percentages, and cumulative percentages
for all the values associated with that variable.
•
It indicates the extent of out-of-range, missing, or extreme values.
•
The mean, mode, and median of a frequency distribution are measures of central tendency.
•
The variability of the distribution is described by the range, the variance or standard deviation,
coefficient of variation, and interquartile range.
•
Skewness and kurtosis provide an idea of the shape of the distribution.
•
The general procedure for hypothesis testing involves the following steps.
•
Formulate the null and the alternative hypotheses, select an appropriate test statistic, choose
the level of significance a, calculate the value of the test statistic, and determine the probability
associated with the test statistic calculated from the sample data under the null hypothesis.
•
Alternatively, determine the critical value associated with the test statistic.
•
Accordingly, make the decision to reject or not reject the null hypothesis, and arrive at a
conclusion.
•
•
Cross-tabulations are tables that reflect the joint distribution of two or more variables.
The general rule is to compute the percentages in the direction of the independent variable,
across the dependent variable.
•
The chi-square statistic provides a test of the statistical significance of the observed
association in a crosstabulation.
•
The phi coefficient, contingency coefficient, Cramer's V, and the lambda coefficient provide
measures of the strength of association between the variables.
•
Parametric and nonparametric tests are available for testing hypotheses related to differences.
•
In the parametric case, the t test is used to examine hypotheses related to the population
mean.
CHAPTER 16 – KEY SENTENCES ANALYSIS OF VARIENCE 533
•
In ANOVA and ANCOVA, the dependent variable is metric, and the independent variables are
all categorical, or combinations of categorical and metric variables.
•
One-way ANOVA involves a single independent categorical variable.
•
Interest lies in testing the null hypothesis that the category means are equal in the population.
•
The total variation in the dependent variable is decomposed into two components: variation
related to the independent variable and variation related to error.
•
The variation is measured in terms of the sum of squares corrected for the mean (SS).
•
The null hypothesis of equal means is tested by an F statistic, which is the ratio of the mean
square related to the independent variable to the mean square related to error.
•
N-way analysis of variance involves the simultaneous examination of two or more categorical
independent variables.
•
A major advantage is that the interactions between the independent variables can be
examined.
•
The significance of the overall effect, interaction terms, and main effects of individual factors
are examined by appropriate F tests.
•
It is meaningful to test the significance of main effects only if the corresponding interaction
terms are not significant.
•
ANCOVA includes at least one categorical independent variable and at least one interval or
metric independent
variable.
•
When analysis of variance is conducted on two or more factors, interactions can arise.
•
An interaction occurs when the effect of an independent variable on a dependent variable is
different for different categories or levels of another independent variable.
•
In balanced designs, the relative importance of factors in explaining the variation in the
dependent variable is measured by omega squared (v2).
•
Multiple comparisons in the form of a priori or a posteriori contrast can be used for examining
differences among specific means.
•
In repeated measures analysis of variance, observations on each subject are obtained under
each treatment condition.
•
This design is useful for controlling for the differences in subjects that exist prior to the
experiment.